Download Copyright by Kyung-ran Kim 2007

Document related concepts
no text concepts found
Transcript
Copyright
by
Kyung-ran Kim
2007
The Dissertation Committee for Kyung-ran Kim Certifies that this is the
approved version of the following dissertation:
The Effects of Advertising and Publicity on
Corporate Reputation and Sales Revenue: 1985-2005
Committee:
Minette E. Drumwright, Supervisor
Ronald B. Anderson
John D. Leckenby
Maxwell E. McCombs
Gary B. Wilcox
The Effects of Advertising and Publicity on
Corporate Reputation and Sales Revenue: 1985-2005
by
Kyung-ran Kim, B.S., M.A.
Dissertation
Presented to the Faculty of the Graduate School of
The University of Texas at Austin
in Partial Fulfillment
of the Requirements
for the Degree of
Doctor of Philosophy
The University of Texas at Austin
August, 2007
Dedication
I dedicate this work to my parents, Mr. Won-ki Kim and Ms. Hyun-goo Lee,
my husband, Seckjun Jang, and my little girl, Jinna K. Jang.
Acknowledgements
First and foremost, I want to thank my advisor Dr. Menette Drumwright. I
thank you for the encouragement and faith you have placed in me throughout my
graduate program. She always made it possible for me to have thoughtful and
qualitative insights. She is a great teacher and scholar. She is patient, wellmannered, and dignified. I am very proud to be her student.
I appreciate Dr. Wilcox who shared his great experience and gave me the
advice and guidance for this dissertation. I also express deep appreciation for the
other committees, Dr. Anderson, Dr. Leckenby and Dr. McCombs who made this
dissertation possible.
v
The Effects of Advertising and Publicity on
Corporate Reputation and Sales Revenue: 1985-2005
Publication No._____________
Kyung-ran Kim, Ph.D
The University of Texas at Austin, 2007
Supervisor: Minette E. Drumwright
With the increasing call for accountability of significant marketing
communication spending, quantifying and measuring the contribution of
marketing communication to market performance is increasingly a requirement
for sustainability in all management practices. In addition, the resource-based
view (RBV) suggests that a firm’s marketing communication creates intangible
market-based assets and that these assets strengthen a firm’s market and financial
performance. Recent developments of the market-based assets theory focus on
corporate reputation as an intangible market-based asset, suggesting that a
favorable reputation is an intangible asset that increases a firm’s performance.
vi
This study examined the effect of advertising and publicity on corporate
reputation and market performance and hypothesized that a firm’s advertising and
publicity generated favorable corporate reputations and high levels of sales
revenues in certain firms. Hypotheses were tested by a time-series analysis using
the panel data of 18 companies over a 21-year period from 1985 to 2005.
The results indicated that advertising and publicity have significant effects
on corporate reputation for certain companies. Other variables, such as a firm’s
dividend yield to investors, market value, diversification, and profitability were
significantly related to assessments of corporate reputation for certain companies,
but the direction of the relationship varied from company to company. For
example, as expected, low dividend yields induce high assessments of corporate
reputation for certain companies. A firm’s current market value also affects
assessments of a firm’s reputation. More diversified companies yield lower
corporate reputations for certain companies.
Regarding the relationship between marketing communication and sales
revenues, advertising and publicity have significant effects on sales revenues for
some companies. A firm’s R&D expenditures, the focus of the firm, and firm size
also showed a significant positive relevance to sales revenues for certain
companies.
vii
Table of Contents
List of Tables ..........................................................................................................x
List of Figures ........................................................................................................ xi
Chapter 1 Introduction .......................................................................................... 1
Chapter 2 Literature Review ..................................................................................7
Marketing Communication and Synergy Effect ............................................ 7
Corporate Reputation ...................................................................................12
Market Performance .....................................................................................18
Chapter 3 Research Hypotheses ...........................................................................26
Research Questions ......................................................................................26
Research Hypotheses ....................................................................................27
Advertising and Corporate Reputation ...............................................27
Publicity and Corporate Reputation ....................................................31
Advertising and Sales .........................................................................38
Publicity and Sales ..............................................................................39
Chapter 4 Methodology ........................................................................................43
Data and Sample ...........................................................................................43
Measurements of Variables ..........................................................................46
Chapter 5 Analyses and Results............................................................................73
Descriptive Analyses ....................................................................................74
Hypotheses Test ............................................................................................97
Additional Analysis ....................................................................................137
viii
Chapter 6 Discussion ..........................................................................................142
Chapter 7 Conclusion .........................................................................................152
Appendix A How Fortune Conducts The Most Admired Survey.......................166
Appendix B Visual Information .........................................................................167
Appendix C Data Transformation ......................................................................185
Appendix D Survey Methodology: The Reputation Institute ............................187
References............................................................................................................189
Vita .....................................................................................................................207
ix
List of Tables
Table 1
Companies Used in the Study..............................................................45
Table 2
Summary of Measures and Data Source..............................................72
Table 3
Durbin-Watson Test for Autocorrelations .........................................105
Table 4
Full Corporate Reputation Models ....................................................111
Table 5
Final Corporate Reputation Models...................................................115
Table 6
Full Sales Revenue Models................................................................121
Table 7
Final Sales Revenue Models..............................................................125
Table 8
Summary of Findings.........................................................................129
Table 9
Results of Granger Tests....................................................................139
Table 10 Results of Granger Tests....................................................................141
Table 11
Summary of Hypotheses Tests by Firm Classification......................145
x
List of Figures
Figure 1
Framework for Analysis - Corporate Reputation ...............................47
Figure 2
Framework for Analysis - Sales Revenue .........................................48
Figure 3
Mean Value of Corporate Reputation by Publicity ............................79
Figure 4
Mean Value of Changes in Advertising by Publicity.........................81
Figure 5
Mean Value of Corporate Reputation by Advertising........................84
Figure 6
Mean Value of Corporate Reputation by Advertising Changes.........85
Figure 7
Mean Value of Corporate Reputation by Advertising Intensity.........85
Figure 8
Mean Value of Sales Revenue by Advertising...................................86
Figure 9
Interaction Effect on Corporate Reputation .......................................90
Figure 10 Interaction Effect on Corporate Reputation .......................................91
Figure 11 Interaction Effect on Corporate Reputation .......................................91
Figure 12 Interaction Effect on Sales Revenue...................................................93
Figure 13 Interaction Effect on Sales Revenue...................................................95
Figure 14 Interaction Effect on Sales Revenue...................................................96
Figure 15 Visual Information............................................................................131
xi
CHAPTER 1
INTRODUCTION
Marketing communication is a key tool in developing a firm’s competitive
advantage. Keller (2001) defines marketing communication at the brand level as
the voice of a brand and the means by which companies can establish a dialogue
with customers concerning their product offerings. Marketing communication can
contribute to greater brand purchase and sustained customer loyalty by imbuing
products and services with additional meaning and value. In a cluttered, complex
marketplace, marketing communication can allow products and services to stand
out and help consumers appreciate their comparative advantages.
There is no doubt that advertising is the foremost marketing
communication tool. Advertising not only signals product and firm characteristics
but also presents firms in a favorable light. As traditional advertising struggles to
catch consumers’ attention, however, public relations has been recognized as
another vital marketing communication tool because of its credibility and
reliability (Economist, 2006; Ries and Ries, 1996). One of the strengths of public
relations in marketing is to generate favorable publicity for products or companies
in media. A company’s message that is presented through the media is often
considered more credible than a direct corporate comtmunication (Gandy, 1982).
1
Due to its source credibility, publicity is likely to have more credibility compared
to advertising. Also, favorable publicity can enhance the effect of advertising. For
example, advertising professionals recognize that news coverage about an
advertising campaign or product can augment media campaign expenditures,
potentially building expectations and heightening awareness of the advertising or
products (Harris, 1998).
Thus, companies invest significant expenditure and effort in marketing
communication. Specifically, spending on pubic relations in America has been
growing dramatically and reached $3.7 billion in 2005 (Economist, 2006). Public
relations spending is forecasted to grow by almost 9% a year. Its growth is faster
than the overall market for advertising and marketing, now worth $475 billion and
growing at 6.7% a year. According to a recent study by Procter & Gamble (Jack,
2005), public relations is surprisingly effective and has a higher return on
investment than any other medium or traditional forms of marketing tools.
Most prior studies have examined the effect of advertising and public
relations at the brand level, such as a consumer’s attitude toward a brand or
behavioral intention about a brand. In particular, they have focused on examining
the superiority of advertising over public relations or vice versa (Cameron, 1994;
Hallahan, 1999; Salmon, Reid, Pokrywcnznski, and Willet, 1985). However, little
attention has been given to the effect of advertising and public relations at the
2
firm level. Marketing communication at the firm level has been studied mainly in
management and strategy-related research. For example, McAlister, Srinivasan,
and Kim (2007) examined the effect of advertising and R&D on the systemic risk
of a firm. Luo and Donthu (2006) defined marketing communication productivity
as the effect of advertising and sales promotions on a firm’s sale level, sales
growth, and corporate reputation. Firms that allocate a large amount of their
resources to advertising and public relations expect their expenditures or efforts to
contribute, ultimately, to the firm’s market performance. That is, with the
increasing call for accountability of significant marketing communication
spending, quantifying and measuring the contribution of marketing
communication to market performance is increasingly a requirement for
sustainability in all management practices. Thus, providing evidence of the
accountability for marketing communication at the firm level has become
important.
In addition, the resource-based view (RBV) suggests that a firm’s
marketing communication creates intangible market-based assets and that these
assets strengthen a firm’s market and financial performance (Barney, 1991; Hall,
1992; Boulding and Staelin, 1995; Erickson and Jacobson, 1992). Recent
developments of the market-based assets theory (Srivastava, Shervani, and Fahey,
1998) focus on corporate reputation as an intangible market-based asset,
3
suggesting that a favorable reputation is an intangible asset that increases a firm’s
performance.
A growing number of studies have argued that good corporate reputations
have strategic value for the firms that possess them (Dierickx and Cool, 1989;
Fombrun, 1996; Roberts and Dowling, 2002; Rumelt, 1987; Weigelt and Camerer,
1988). A company’s reputation has long been recognized as a critical factor in
successful marketing. Corporate reputation has been believed to affect the buyer’s
expectations with respect to the quality of its offerings (Nelson 1970; Margulies
1977; Shapiro 1982, 1983; Yoon, Guffey, and Kijewski, 1993). Page and Fearn
(2005) suggested that it is very difficult to achieve strong product brand equity
with a poor corporate reputation. Therefore, corporate reputation is one
appropriate outcome measure for determining the effect of marketing
communication.
This study attempts to examine the effect of advertising and public
relations on corporate reputation and market performance. With respect to this,
two research questions are addressed. The first research question is, “How do
advertising and publicity contribute to corporate reputation?” The second research
question is, “How do advertising and publicity generate sales revenue?” This
study hypothesizes that a firm’s advertising and publicity can generate favorable
corporate reputations and high levels of sales revenues.
4
Hypotheses were tested by a time-series analysis using the panel data of
18 companies over a 21-year period from 1985 to 2005. Eighteen companies that
have a reputation rating for each year in the 21-year period from 1985 through
2005 were selected from Fortune’s America’s Most Admired Companies survey.
Then, data on the advertising expenditures, publicity index, corporate reputation,
sales revenue, and other firm variables were obtained from multiple sources:
COMPUSTAT database, Fortune’s America’s Most Admired Companies Survey,
and the online news database Lexis-Nexis. The main purpose of this study is to
provide a comprehensive analysis of the relationship between marketing
communication and corporate reputation and between marketing communication
and sales revenue by selecting a significant subset of predictor variables.
This is the first empirical study to use a multi-industry sample of firms
over a 21-year period to address the question of whether higher advertising and
favorable publicity generate favorable assessments of corporate reputation and
increase sales revenues. Also, this is the first study to attempt to examine the
simultaneous effect of advertising and publicity using the longitudinal panel data
at the firm level. This study provides a timely empirical examination of the effect
of advertising and public relations, in that they are the most representative
marketing communication tools, and synergy or combined effect has been a
primary research agenda in integrated marketing communication.
5
Chapter 2 reviews the general literature on the importance of advertising
and publicity, corporate reputation, and the effect of marketing communication on
market performance. On the basis of the literature review, Chapter 3 proposes
research questions and hypotheses. Sample composition and measurements of
variables included in the study are presented in the methodology section of
Chapter 4. Chapter 5 describes analyses procedures and provides the results of
descriptive analyses and hypotheses testing. Chapter 6 discusses the results of the
study and provides theoretical and managerial implications. Finally, Chapter 7
suggests the limitations and directions for further study.
6
CHAPTER 2
LITERATURE REVIEW
Marketing Communication and Synergy Effect
Most companies try to achieve a competitive advantage through various
activities. Marketing communication, a key tool in developing a competitive
advantage, consists of all the promotional elements in the marketing mix that
involve the communication between an organization and its target audiences on
all matters that affect marketing performance (Pickton and Broderick, 2001).
Keller (2001) suggested that marketing communication is the voice of a brand and
the means by which companies can establish a dialogue with consumers
concerning their product offerings. That is, marketing communication is the
means by which firms attempt to inform, persuade, incite, and remind consumers
about the products and companies. Through a marketing mix, including elements
such as advertising, public relations, promotions, database marketing, etc.,
marketing communication enables companies or products to transcend their
physical natures and to provide products and services with additional meaning
and value. Therefore, in a cluttered, complex marketplace, marketing
communication can contribute to greater brand purchases through customer
7
satisfaction and sustained consumer loyalty, which is the competitive advantage
marketing communication ultimately tries to attain.
In recent years, as the role of synergy has been stressed as a key to
maximizing competitive advantage (Aaker, 1995), integrated marketing
communication has been recognized as a strategic tool in ensuring synergy.
Consequently, integrated marketing communication has been recognized as one of
the marketing communication strategies that provides a competitive advantage in
a complex marketplace (Agres and Dubitsky, 1996; Reid, 2003). In other words,
through integrated marketing communication, a firm can attain synergy among all
of its marketing communication activities and decisions, and that synergy can lead
to performance benefits. Some research has found positive relationships between
integrated marketing communication and market performance such as sales,
productivity, brand strength, customer loyalty, etc. (Duncan and Moriarty, 1997;
Eagle and Kitchen, 2000; Reid, 2003).
Synergy or interaction is the fundamental concept of integrated marketing
communication and has been considered the foremost research agenda. Much
integrated marketing communication academic literature has mentioned that
integrated marketing communication is the strategic coordination of multiple
communication voices, pursuing synergy by integration. That is, the goal of
employing multiple marketing communication tools is to induce the synergy
8
effect or mutual reinforcement to create the greatest persuasion effect (Carlson et
al, 1996; Cook, 1996; Duncan and Everett, 1993; Eagle et al., 1999; Hutton, 1996;
Naik and Ruman, 2003; Nowak and Phelps, 1994; Pickton and Hartley, 1998;
Reid, 2003; Schultz, 1996; Schultz and Kitchen, 1997; Stewart, 1996; Moriarty,
1996; Schultz, Tannenbaum, and Lauterborn, 1992; Thorson and Moore, 1996;
Gaywood, Schultz, and Wang, 1991).
Synergy is defined as the interaction of two or more agents or forces so
that their combined effect is greater than the sum of their individual effects
(American Heritage College Dictionary, 1997). Stammerjohan, Wood, Chang,
and Thorson (2005) defined synergy as a positive response to a campaign that is
greater than the sum of separate expected responses based on the use of each
communication tool. However, eliciting how the synergy operates has been
difficult and elusive. Moreover, little has been examined regarding the synergy
effect of different, multiple marketing communication activities.
With respect to the study of synergy effects in marketing communication,
the main focus has been cross media studies that have examined synergies
resulting from the use of multiple media in an advertising campaign. Bhargava
and Donthu (1999) examined the effect of outdoor media on sales. Edell and
Keller (1989) examined media interactions in an advertising campaign employing
TV and radio to understand how advertising campaigns should be coordinated
9
across media. They found that when consumers are exposed to a TV ad and later
hear the audio on the radio, the audio track serves as a retrieval cue for the video
representation of the ad and an associated reaction stored in memory from the TV
ad exposure. With respect to the use of multiple media in an advertising campaign,
in general, it has been reported that print advertising can enhance the
effectiveness of TV advertising when both ads are well-coordinated (Confer,
1992; Confer and McGlathery, 1991). Also, a few researchers support the fact that
using multiple media will improve advertising effects on consumers’ memorybased judgments (Tavassoli, 1998; Tavassoli and Lee, 2003). Chang and Thorson
(2004) examined television and Web advertising synergies and found that their
synergy leads to higher attention, higher perceived message credibility, and a
greater number of total positive thoughts than did mere repetition in a single
medium.
As mentioned above, the central research agenda of integrated marketing
communication is to explore how synergy/interaction effects have been generated.
Nonetheless, few studies have examined the synergy effects of multiple marketing
communication tools including advertising, sales promotion, public relations,
direct marketing, personal selling, etc. While a few studies have considered
multiple promotional tools, those studies focus on the relationship between
advertising and sales promotion (e.g., advertising and sales promotion ratio).
10
Furthermore, these studies have been confined to the area of mathematical
modeling research (Ailawadi, Farris, and Parry, 1994; Balasubramanian and
Kumar, 1990; Farris and Albion, 1981). In recent years, as the interest in
integrated marketing communication effects has risen, a few researchers have
examined the interaction/synergy effect of different marketing communication
tools on consumers’ information processing by using a controlled experimental
setting. Stammerjohan, Wood, Chang, and Thorson (2005) explored the combined
effect of two marketing communication tools, publicity and advertising, on
attitude toward the ad and attitude toward the brand, and found synergetic effects
between publicity and advertising. Jin (2004) detected the synergy effect between
marketing publicity and advertising by examining the effects of Super Bowl
advertising campaign information in news stories on consumers’ memory of the
subsequent ads.
As mentioned previously, despite an increasing interest in integrated
marketing communication, there has been little research on the synergy effect of
multiple marketing communications, particularly in advertising and public
relations, at the firm level. The majority of previous studies regarding the effects
of advertising and public relations have examined the superiority of advertising
over public relations or vice versa (Cameron, 1994; Hallahan, 1999; Salmon, Reid,
Pokrywcnznski, and Willet, 1985). In recent years, two studies examined the
11
synergy effects of two marketing communication tools, advertising and pubic
relations (Jin, 2004; Stammerjohan, Wood, Chang, and Thorson, 2005). However,
these studies examined the synergy effect of multiple marketing communication
tools (advertising and public relations) at the brand level, rather than at the firm
level. No research has investigated the cumulative synergy effect of multiple
marketing communications at the firm level. This study explores the effect of
advertising and public relations using cumulative corporate level data.
Corporate Reputation
A growing number of studies have argued that good corporate reputations
have strategic value for the firms that possess them (Dierickx and Cool, 1989;
Fombrun, 1996; Roberts and Dowling, 2002; Rumelt, 1987; Weigelt and Camerer,
1988). A firm’s reputation can be used as a means of building source credibility,
which in turn influences communication effectiveness. Thus, in the marketing
literature, company reputation has long been recognized as a critical factor in
successful marketing. Corporate reputation has been believed to affect the buyer’s
expectations with respect to the quality of a firm’s offerings (Nelson, 1970;
Margulies, 1977; Shapiro, 1992; Yoon, Guffey, and Kijewski, 1993). According
to the resource-based view, firms with valuable and rare assets possess a
12
competitive advantage and may expect to earn superior returns. Those assets are
also difficult to imitate and may enable sustained superior financial performance
(Barney, 1991; Grant, 1991). Therefore, intangible assets such as good reputations
are critical not only because of their potential for value creation but also because
of the difficulty of replication by competing firms.
Although many academic scholars have attempted to identify the nature
and value of corporate reputation, there is no clear understanding about the
function and role of corporate reputation, particularly in marketing. In marketing
and communication, “reputation” has been used interchangeably with the terms
“image,” “brand,” “brand equity,” “identity,” and “corporate identity” (Gedulig,
1999; Huey, 2002; Jeffries-Fox Associates, 2000; Vercic, 2000; Argenti, 2003).
Yoon, Guffey, and Kijewski (1993) also mention that the role of reputation in the
marketplace is very similar to brand goodwill or brand equity, particularly when
the company name is a part of the brand identification. Jeffries-Fox Associates
(2000) conducted a content analysis to compare the terms “reputation,” “brand
equity,” and “goodwill.” They found that the same component ideas are
associated with brand equity and corporate reputation, and the terms are used
interchangeably. They concluded that public relations managers are more likely to
use the term “reputation” and marketing managers to use “brand equity.” Huey
(2002) suggested that reputation is based on performance, whereas brand equity is
13
based more on communication effects than in actual performance. On the website
of the Reputation Institute, Fombrun said that a brand describes the label that a
company uses to distinguish itself from rivals with its customers
(http://www.reputationinstitute.com/main/home.php). A company has many
different images and can have many brands. In contrast, a corporate reputation
signals the overall attractiveness of the company to all of its audiences, including
employees, customers, investors, reporters, and the general public. A corporate
reputation, therefore, reconciles the many images people have of a company, and
conveys the relative prestige and status of the company.
Corporate reputation is based on how the company conducts, or is
perceived as conducting, its business (Morley, 1998). In today’s corporate world,
there is little or no distinction between product qualities, prices, or technologies.
Therefore, a company’s reputation can be not only the primary basis for a
consumer’s purchasing decision but also everything from stock value of the
company to employee satisfaction or attitude toward the brand or product itself.
There are two primary perspectives about corporate reputation. The first
perspective views corporate reputation as a general organizational attribute that
reflects the extent to which external stakeholders see the firm as good and not bad.
According to this view, reputation is defined as an impression of pubic esteem or
high regard judged by others (Merriam Webster’s Collegiate Dictionary 1996,
14
p.1001). American Heritage Dictionary defines reputation as the general
estimation in which one is held by the public. Working from this context, Weiss,
Anderson, and Maclnnis (1999) defined reputation as the extent to which a
company is held in high regard or esteem. Fombrun (1996, 2001), Roberts and
Dowling (2002), and Fombrun and Van Riel (1997) defined reputation as a
collective representation of a company’s past actions and future prospects that
describe the firm’s overall appeal to all its key stakeholders when compared to
other leading rivals. In other words, corporate reputation describes how key
stakeholders interpret a company’s initiatives and assess its ability to deliver
valued outcomes. These definitions imply that corporate reputation is developed
through complex interactions between a firm and its stakeholders over time. That
is, corporate reputation is developed by the dissemination of information about
the past and current actions of the firm among stakeholders (Deephouse, 2000;
Fombrun, 1996).
Secondly, economists views corporate reputation as an outcome of a
competitive process in which a firm signals its important features to stakeholders
(Spence, 1974). Due to the presence of incomplete and asymmetric information in
markets, stakeholders are unsure of a firm’s ability to deliver reliable and quality
products or services. Consequently, reputation is a way to interpret and make
attributions about a firm’s actions (Kreps and Wilson, 1982). Shapiro (1983)
15
pointed out that the importance of a company’s reputation increases under
conditions of imperfect information. When performance information is not
perfectly disseminated among the customers, the marketer’s reputation is used as
a guideline to form expectations of quality. This is particularly important when
information search costs are high (Smallwood and Conlisk, 1979).
Unlike the first perspective, which relies on the interaction between a firm
and its stakeholders to create perceptions about the reputation of that firm, the
economic perspective focuses on the role of signaling in uncertain markets.
However, both perspectives appear to agree that a favorable corporate reputation
is developed by stakeholders’ impression of the firm’s past and current actions to
behave in a certain manner in the future.
Several studies confirm the benefits associated with good reputations. A
positive reputation is important for a competitive advantage because it signals
stakeholders about the attractiveness of the firm, and stakeholders are then more
willing to contract with the firm (Fombrun and Shanley, 1990; Weight and
Camerer, 1988). Favorable reputation has been linked with a firm’s ability to
survive in crisis (Shrivastavas and Siomkos, 1989), positive customer attitude
toward the company’s products and salespeople (Brown, 1995), enhanced buying
intentions (Yoon, Guffey, and Kijewski, 1993), and choice (Traynor, 1983). Also,
by signaling consumers about product quality, a favorable reputation may enable
16
firms to charge premium prices (Klein and Leffler, 1981; Milgrom and Roberts,
1986; Shapiro, 1983), attract better applicants (Stigler, 1962), enhance their
access to capital markets (Beatty and Ritter, 1986), aid rapid market penetration
(Robertson and Gatignon, 1986), and attract investors (Milgrom and Roberts,
1986). Page and Fearn (2005) suggest that it is very difficult to achieve strong
product brand equity with a poor corporate reputation. In addition, a favorable
corporate reputation may be used to increase the perception and evaluation of the
firm by the media (Deephouse, 2000). In short, a favorable corporate reputation
signals to stakeholders the attractiveness and effectiveness of a firm and positions
the firm to benefit from these stakeholders in the future.
These benefits associated with good reputation make a company engage in
explicit reputation building activities, because reputation perceptions are linked
with outcomes deemed important to the firm (Bromely, 1993; Yoon, Guffey, and
Kijewski,1993). An organization with an unfavorable reputation may engage in
actions that enhance its reputation, and even a firm with a good reputation may
engage in actions designed to maintain and enhance its reputational effect. Yoon,
Guffey, and Kijewski (1993) suggested that marketing communication such as
advertising is a major source of reputation. Fombrun and Shanley (1990) and
Kotha et al. (2001) showed that media exposure and advertising or marketing
investments influenced the development of corporate reputations.
17
These previous studies indicate that the effective management of corporate
or brand identification is essential for maintaining company reputation. Based on
prior studies, this study argues that corporate reputation can be managed by
actively engaging in marketing communication activities such as advertising and
public relations.
Market Performance
“How does advertising work?” has been the most important and heated
research question in advertising studies. In fact, it is not an exaggeration to say
that the whole history of advertising research has revolved around this general
question of advertising effectiveness. Two approaches have been taken – an
economic approach and a psychological approach. Psychological approaches
concern how people feel, think, respond to, and use marketing communication to
make purchase decisions, whereas economic approaches, or market response
models, concentrate on how marketing communication can be strategically
managed to improve the value of products and services from the managerial
perspective. According to psychological response models, advertising or public
relations has some intermediate effects, such as cognition, affect, and experience,
before it affects behavior. In contrast, economic approaches do not consider any
18
intermediate effects. They directly relate marketing communication to behavioral
measures such as sales, market share, and brand choice. Historically, economic
and psychological approaches have been conceptualized as opposite sides of the
advertising effectiveness research spectrum, and they appear to be two
incompatible research streams.
In the real world, however, it is rarely easy to establish such a clear
distinction between economic and psychological approaches. Rather, they are
often complementary. For example, Zahay, Peltier, Shcultz, and Griffin (2004)
confirmed this fact by asserting that the distinction between transactional (sales)
and relational (psychographic customer profile) data is less clear. They mention
that psychographic customer profiles can be inferred from transactional data, and
similarly, relational data such as customer satisfaction surveys and personal
contacts provide an opportunity to learn about the transactional characteristics of
customers as well. Therefore, these two research streams should be closely related
and contribute to improving a firm’s market performance in areas such as sales,
market share, and profit.
Numerous academic researchers and professionals have examined the
effect of advertising on market performance. Literature about advertising and
market performance such as sales or market share has been well established.
Since the classic AIDA model was introduced, researchers have shown a
19
tremendous amount of interest in predicting the advertising-sales relationships. In
the 1960s and 1970s, academic researchers suggested various statistical models to
explain the advertising-sales relationships, but they failed to reach a general
consensus. Rather, their studies revealed that other marketing activities and
exogenous variables, such as economic conditions, the level of competition in the
market, and geographic or demographic variables, should be considered in
examining the advertising-sales relationships (Bass, 1969; Telser, 1962; Palda,
1964; Quandt, 1964). Since then, more reliable data and more improved statistical
methods have been employed, and other marketing mix variables and market
performance measure were added to find the advertising-sales relationships (Bass
and Clarke, 1972; Rao and Miller, 1975).
Since the relationship between advertising spending and sales has been of
great interest, many academic researchers have employed economic approaches
(Asumus et.al., 1984; Leone and Shultz, 1990; Lodish et al., 1995; Sethuraman
and Tellis, 1991; McDonald, 1992; Parker and Gatignon, 1996). However, these
studies have not shown consensus regarding the advertising-sales relationships.
For example, research has shown different results with respect to the carryover or
lagged-effect. Assmus, Farley, and Lehmann (1984) suggested three to fifteen
month-carryover effects on sales, whereas Leone (1995) insisted that the
advertising effect on sales disperses after six to nine months. Winer (1979)
20
suggested that even though the carryover effect of advertising would decline over
time, current advertising effects would increase during the same period. Dekimpe
and Hanssens (1995) suggested that the effect of advertising on sales did not
disperse within a year. Also, a few studies suggested that the results regarding
advertising effects on sales were different depending on brands. A meta analysis
investigating 389 real world split cable TV advertising revealed that while
increased advertising weight increased the sales of established brands in only 33
percent of the cases investigated, there was a 55 percent increase for new brands
(Lodish et al., 1995). Vakratsas and Amber (1999) pointed out that the results of
these studies were different depending on the product or product category
investigated or the data used in the study. Even though there have been no
consistent results on the advertising-sales relationship, valuable work on the
advertising-sales relationship has been done by many researchers.
Compared with the studies on the effect of advertising on sales, literature
about the effects of public relations on market performance is not well established.
As the interest in public relations and public relations budgets has increased,
accountability for public relations has become a more important issue in business
organizations.
The public relations literature sees the impact of public relations both in
financial terms and in terms of long-term credible relationships with key publics.
21
The economic performance typically refers to dollars and the monetary return on
investments given back to a firm (Grunig, Grunig, and Dozier, 2002). There is
some incongruence in trying to measure the effect of public relations on the
organization in terms of economic performance.
Some public relations scholars and professionals do not believe that
money invested in pubic relations can be linked to a consistent, yearly monetary
return on investment. Many CEOs agree that public relations is a contributing
factor, rather than the determinant of organizational effectiveness (Campbell
1993). Furthermore, there is little empirical research that has directly related the
public relations budgets or expenditures to a company’s economic performance.
The basic perspective of these studies implies that a goal of public relations is not
a direct increase of the bottom line, but that public relations can contribute to a
firm’s market performance by achieving its goals of good reputation or good
relationships with stakeholders. That is, the effects of public relations on market
performance have been inferred by examining the relationship between outcome
measures (e.g., goodwill, social responsibility) of public relations and market
performance.
For example, Preston (1981) suggested that public relations may make an
indirect contribution to organizational effectiveness and emphasized that social
responsibility is an indirect contribution of public relations. He reviewed the
22
relationship between socially relevant behaviors of companies and their economic
performances and found that responsible behavior indirectly affects a firm’s
performance. Similarly, Tuleja (1985) stated that ethical behavior formed through
public relations helps companies enhance their economic performance indirectly
by developing more productive employees and avoiding excessive governmental
and nongovernmental regulations. Hon (1997) suggested that attributes of public
relations effectives were defined as managing risks, building relationships,
fostering media relations, earning respect, increasing understanding, achieving
goals, affecting registration, and disseminating appropriate messages. This
research established building relationships and earning respect as two major
dependent variables for public relations effectiveness. Vercic (2000) posited that
trust as an attitudinal measure of public relations explains the financial
performance of a corporation. He found that trust has no direct relationship to
organizational performance, but it determines the organization’s performance in
certain contexts. Kim (2001) established a two-stage model to measure the
economic value of public relations by testing two relationships: (1) the impact of
public relations expenditure on reputation as a public relations goal and (2) the
economic impact of reputation on companies’ bottom lines. His study found that
public relations expenditure affects the company’s reputation positively, and the
23
company’s reputation affects the company’s revenue positively. He concluded
that public relations expenditures indirectly affect a firm’s revenues.
The studies mentioned above assume that the public relations goal is not to
increase a firm’s economic performance directly but to contribute to its
performance by achieving public relations goals. However, the direct relationship
between public relations and market performance has still been of key interest
among marketing scholars and practitioners. Moreover, as integrated marketing
communication has received a great deal of interest from academic researchers
and practitioners, performance measures based on the effects of integrated
marketing communication have been the hot issue. With respect to integrated
marketing communication and performance issues, some researchers have insisted
that integration in marketing communication should lead to some level of superior
business performance (McArthur and Griffin, 1997; McGoon 1998; Pickton and
Hartley, 1998; Kitchen and Schultz, 1999; Eagle and Kitchen, 2000; Low, 2000).
In other words, through integrated marketing communication, a firm can attain
synergy from all of its marketing communication activities, and in turn, this
synergy leads to performance benefits. However, despite the increasing interest in
the link between integrated marketing communication and economic performance
at brand-levels or firm-levels, there has been little empirical evidence to support
this integrated marketing communication-performance relationship. Thus, this
24
study attempts to examine the direct effect of public relations on market
performance.
In sum, with respect to the studies on the advertising-sale relationships,
there has been no consensus in predicting the relationship between advertising
and sales. Data availability, other exogenous variables, or other marketing mix
variables have contributed to this incongruence. In public relations studies, the
relationship between public relations and market performance has been
demonstrated by examining the indirect effects caused by public relations, such as
relationships, reputation, or trust, rather than by examining the direct impact of
public relations itself on market performance.
On the basis of prior studies on marketing communications and market
performance, this study argues that there is a direct positive relationship between
marketing communication and market performance. Research hypotheses are
derived from the notion that firms engage in reputation building activities
including advertising and public relations to improve their overall market
performance.
25
CHAPTER 3
RESEARCH HYPOTHESES
Research Questions
The major goals of this study are to provide a comprehensive analysis of
the effects of marketing communication – advertising and publicity – on corporate
reputation and sales revenue. Based on the goals, two research questions were
established: (1) “How do advertising and publicity contribute to corporate
reputation?” and (2) “How do advertising and publicity generate sales revenue?”
In order to answer these research questions, the study proposes four research
hypotheses.
Hypotheses 1 and 2 address the first research question: the relationship
between marketing communication and corporate reputation. The first hypothesis
predicts a positive relationship between advertising expenditure and corporate
reputation. The second hypothesis focuses on the impact of publicity and
corporate reputation.
Hypotheses 3 and 4 were proposed to answer the second research
question: the relationship between marketing communication and market
performance. The third hypothesis asserts a positive relationship between
26
advertising and sales revenue. The fourth hypothesis examines whether there is a
positive relationship between publicity and sales revenue.
Research Hypotheses
Marketing Communication and Corporate Reputation
Advertising and Corporate Reputation
Much marketing and advertising literature has explored the value of
brands and the notion of brand equity to assess marketing communication effects,
especially the effect of advertising. For example, corporate advertising pertaining
to the company’s market coverage, market share, or brand popularity often is
helpful in building an overall image. Claims of being popular among customers
(Raj, 1985) or being innovative (Porter, 1985) support the marketer’s efforts to
increase brand loyalty. A reputation of brand leadership elicits a favorable attitude
toward advertising (Simon, 1970), suggesting that companies with higher quality
products benefit more from advertising spending (Shugan, 1985). Kijewski (1985)
reported that industrial businesses with higher levels of advertising enjoyed higher
levels of perceived quality and higher relative prices for any given level of
perceived quality. Hoch and Ha (1986) suggested that advertising has a significant
27
effect on customers’ perceptions of quality when they experience ambiguous
evidence about the product’s quality. Winters (1986) reported that brand
advertising is effective for enhancing the marketing image for a company, while
corporate advertising is effective for improving the social conduct image of the
company.
Since reputation has been regarded as having the same component as
brand equity (Jeffries-Fox Associates, 2000), marketing communication,
especially advertising, also has great value to a corporation. There have been
many reputation studies. For example, marketing and management researchers
have investigated how people form perceptions of a company’s reputation and
how that reputation affects consumers’ perceptions of price unfairness and
influences managers’ decision-making (Campbell, 1999). However, relatively
little attention has been given to the relationship between advertising and
corporate reputation. Little empirical research has examined how marketing
communication, especially advertising, affects corporate reputation from firms’
point of view.
The public constructs reputations from available information about a
firm’s activities originating from the firm itself, from the media, or from other
sources. Since different sectors of the public attend to different features of firms’
performance, reputations reflect firms’ relative success in fulfilling the
28
expectations of multiple stakeholders (Freeman, 1984). A study by Fombrun and
Shanley (1990) investigating the factors that influence corporate reputation found
that publics construct reputation on the basis of corporate strategy signals.
Differentiation through advertising has been considered the most representative
signal of corporate strategy.
Both brand and corporate advertising help firms develop strategic
positions that are differentiated from their competitors’ and that provide them
with a measure of goodwill from consumers and other stakeholders (Rumelt,
1987). Also, advertising helps induce a protected strategic position that stabilizes
sales. Advertising not only signals product and firm characteristics in ways that
can reduce stakeholders’ search cost for information but also presents firms in a
favorable light. Advertising is viewed as a source of product and imaging cues
designed to influence the perceptions of external publics. Advertising can further
reinforce the information that customers have already acquired with respect to
brands or companies. Often, advertising is used as a tool to inform about product
quality. A sufficient level of advertising implies a significant investment on the
part of the firm.
While managing a corporate reputation involves many factors, research
has suggested that advertising has been successful in promoting corporate
reputation to various audiences. Many academic researchers have supported the
29
idea that companies rely on advertising to develop their reputations. Podolny
(1993) suggested that the positive interactions between reputation and salient firm
features such as advertising provide a firm with greater incentive to engage in
actions that further enhance its reputation. According to Schumann, Hathcote, and
West (1991), advertising can help better position American products against the
competition, to meet increased pressure from consumer groups and politicians,
and to repair the corporate reputation of American companies that are criticized
for their roles in creating adverse environmental conditions. Goldberg and
Hartwick (1990) indicated that potential customers receive advertising claims
more favorably if the reputation of the firm making those claims is more positive.
They found evidence of a reputation effect by investigating the combined effects
of a company’s reputation and advertising on product evaluations. Subjects who
formed a negative evaluation of the company based on a bad reputation found the
claims of advertising less credible and rated the products less favorably than those
who received positive reputation information about the company.
Fombrun (1996) asserts that a company is held in high regard and esteem
when it is visible and credible. Since advertising is one of the foremost strategies
in establishing the visibility and credibility of a company, an antecedent helps to
establish the link from advertising to reputation. Chaudhuri’s (2002) study found
that brand advertising enhances a brand’s reputation, and reputation, in turn,
30
augments the effectiveness of advertising by perceptually enhancing a brand
within its product category and leading to greater sales for the brands. Therefore,
a hypothesis regarding advertising and corporate reputation is established as
follows:
Hypothesis 1: Advertising will have a positive impact on corporate
reputation.
Public Relations and Corporate Reputation
Public relations professionals have consistently asserted the superiority of
news articles. Generally, this belief stems from the assumption that third-person
endorsements are more credible than those from the source itself. When mass
media endorse a product or a company, the product or company gains public
support from the third-party endorsement for the message. That is, the
prominence given to media relations in public relations activities lies in public
relations professionals’ strong belief in the impact of news media. For this reason,
marketing managers and public relations professionals frequently count the
number of media clippings about their product or company. The typical public
relations measurement focuses on counting clippings and circulation figures and
doing some message analysis. Given the high proportion of pubic relations
31
activities that are still focused on media relations and publicity, media content
analysis is one methodology or tool for evaluating public relations. Media content
analysis can provide valuable insights into what is likely to be on the public
agenda in the future. This is why public relations professionals regard media
relations as one important area of public relations; therefore, the present study
examines the effect of public relations in terms of publicity.
The media have a powerful effect on the issues we pay attention to. A
well-known study conducted by McCombs and Shaw (1972) found an almost
perfect correlation between media coverage and the concerns that voters
expressed. This study was the initial research that confirmed the agenda setting
role of the media. It implies that the media have a strong effect on shaping the
publics’ view of events and their importance and that the number of times a story
is presented in the news affects peoples’ perception of an event’s importance
regardless of what is said about the topic. More recent agenda-setting studies have
moved beyond issue salience to examine media effects on attitudes and behaviors
and further the media’s influence on the social construction of reality (Gamson,
Croteau, Hoynes, and Sasson, 1992; Roberts, 1992; Smith, 1995).
Agenda-setting studies can be used in marketing communication research.
Many mass communication studies suggest that the media record public
knowledge and opinions about firms and also influence public knowledge and
32
opinions about firms. In addition to political communication setting, about which
most prior agenda setting studies have been conducted, the agenda setting can be
applied to the business communication environment. Many researchers have
pointed out that business news coverage is important to organizations attempting
to manage issues because much of what consumers and other external
stakeholders learn about companies and the issues that surround them comes from
the news media (Chen and Meindl, 1991; Deephouse, 2000; Dutton and Dukerich,
1991; Fombrun and Shanley, 1990). Carroll and McCombs (2003) addressed a
few propositions emphasizing the importance of news coverage in the business
sector.
The fact that media coverage influences public knowledge and opinion is
applicable to reputation because media coverage is a reasonable indicator of the
publics’ knowledge and opinions about firms (Deephouse, 2000). Fombrun and
Shanley (1990) and Fombrun and Abrahamson (1988) mentioned that the media
act not only as vehicles for advertising and mirrors of reality reflecting firms’
actions, but also as active agents shaping information through editorials and
feature articles. Fombrun and Shanley (1990) and Wartick (1992) assumed that
the media possess information available for processing by stakeholders in making
reputational assessments, which is consistent with the signaling role of reputation.
Deephouse (2000) developed a concept called media reputation, which is defined
33
as the overall evaluation of a firm presented in the media, and found that media
reputation is a resource that increases business performance. That is, the media
have powerful effects on corporate visibility. On the one hand, companies
regularly advertise their products and activities, thereby projecting attractive selfconcepts and images to consumers. On the other hand, the media interpret,
amplify, and shape news stories through commentaries that affect how consumers
think about companies.
When we think about a single company, we choose specific criteria to
evaluate the company. While various instruments have been proposed to address
this issue, Fortune magazine’s corporate reputation has been one of the bestknown measures. Staw and Epstein (2000) found that companies with much
media coverage were more admired, perceived to be more innovative, and rated
more highly in management quality in Fortune magazine’s annual Most Admired
Company survey. Fortune’s Most Admired Company survey will be discussed
further in methodology section.
In addition to Fortune’s corporate reputation, other reputation indices
explain the relationship between news coverage and corporate reputation. For
example, The Reputation Institute has confirmed a positive relationship between
corporate reputation and media visibility. The Reputation Institute tests six
dimensions or attributes on thousands of people, online, by phone, and in personal
34
interviews. Based on these tests, they create an overall reputation score called the
Reputation Quotient (Fombrun, 1996). They confirm that many of the most
visible companies that were among the top-rated companies in the RQ
(Reputation Quotient) Project also earned top scores in media visibility. In other
words, the pubic tends to notice the companies that are put on the agenda by the
media and also tends to give higher ratings to those companies that get more
favorable press coverage.
Many pubic relations professionals and researchers insist that the goal of
public relations is to improve the organization’s reputation. According to Hon’s
(1997) study, CEOs believed that the ultimate goal of public relations was to
communicate the image of the organization. The organization’s image could be
interpreted as its reputation because image does not refer to symbolic identities
such as company and brand names. Public relations academic researchers do not
use the term “image.” Instead, they use “reputation” as a better way to define
corporate image because they believe it represents behavioral relationships with
publics (Grunig, 1993). Because of negative connotations related to pubic
relations, Grunig (1993) replaced “image” with “symbolic relationships” and
“behavioral relationships.” In this context, reputation implies substantive
behavioral relationships, not superficial symbolic activities. Hutton, Goodman,
and Alexander (2001) mentioned reputation management as the new face of
35
corporate public relations. Grunig (1993) also insisted that reputation is one of the
dependent variables of public relations effectives.
As mentioned above, the media play a major role in forming the public
image of organizations. According to Fombrun and Shanley (1990), institutional
signals, which make firms more or less visible, attractive, and socially responsive,
are some of the factors that influence corporate reputation. They said that media
visibility is one of the institutional signals to which marketing communication
managers or professionals have to pay attention. Therefore, companies attempt to
influence their various audiences by disseminating information through networks
of interpersonal relations or interlocking corporate ties (Mizruchi and Schwartz,
1987) and through press articles and mass media presentations (McQuail, 1985).
Thus, many companies have public relations departments that provide a steady
stream of information to the media.
The information reported in the media comes from various sources.
Company press releases from public relations departments provide information to
the media (Shoemaker and Reese, 1991). Stakeholders are another source.
Individuals provide their opinion letters to the media. The government and its
specialized agencies evaluate firms. Reporters, editors, and columnists write news
and feature stories about firms. Therefore, specific stories that appear in the media
36
can contain conflicting information, including positive or negative information
about the firm and its activities.
The media do not simply passively record events through unbiased
reporting. Both the mass media and specialized publications disseminate
information and evaluation of firms. They report selectively and interpret what
they observe according to their interests. Media not only convey information but
also actually make and present reputational assessments to their audiences. Media
favorability indicates the overall evaluation of a firm presented in the media
resulting from the stream of media stories about the firm. Deephouse (2000)
suggested the evaluative dimension of news coverage in terms of unfavorable and
favorable. He used “favorable” to indicate that a firm was praised for its actions
or that the firm was associated with activities that should raise its reputation. He
used “unfavorable” when an organization was criticized for its actions or
associated with actions that should decrease its reputation.
Just as the availability or amount of information biases individuals’
judgments (Tversky and Kahneman, 1974), evaluations channeled through the
business press and the mass media may bias the public’s construction of corporate
reputations. Firms frequently and nonnegatively mentioned or praised by the
media might therefore develop better reputations than other firms, because they
occupy more central positions in a social network (Burt, 1983). A hypothesis
37
regarding the relationship between publicity and corporate reputation is
established.
Hypothesis 2: Favorable publicity will have a positive impact on corporate
reputation.
Marketing Communication and Market Performance
Advertising and Sales Revenue
As discussed previously, while a number of studies examined the
relationship between advertising and market performance, there has been little
consensus on the advertising-sales relationship. In addition, little empirical
research has investigated the simultaneous effect of both advertising and publicity
on market performance. Prior research regarding the marketing mix and market
performance has been mainly focused on advertising and sales promotion. Even
though a few recent studies explored the synergy effect of advertising and
publicity, their research focused on psychological outcome measures, such as
brand attitude or advertising attitude, rather than market performance (Jin, 2004;
Stammerjohan, Wood, Chang, and Thorson, 2005).
38
In recent years, there are only a few studies examining the relationships
among advertising, brand reputation, and such outcome variables as market share
and relative price. Chaudhuri’s study (2002) suggested that brand advertising was
both directly and indirectly related to brand sales, with the indirect linkage
occurring through the construct of brand reputation. Smith and Park (1992) found
a positive relationship between differentiation through advertising and market
share. Their study explained that differentiated brands lead to greater market share
and relative price because they increase brand reputation, which leads to superior
outcomes over competition.
Based on prior research, this study asserts a hypothesis regarding
advertising and sales revenue.
Hypothesis 3: Advertising expenditure will have a positive impact on sales
revenue.
Publicity and Sales Revenue
Even though there have been arguments that the objectives of strategic
public relations and corporate communication should extend beyond achieving
immediate financial outcomes, measuring pubic relations value as a direct
monetary return is still the most attractive form of evaluation. Furthermore, as the
39
importance of pubic relations has been emphasized and public relations spending
have increased, the necessity of accountability of public relations has risen.
Companies expect more substantial and immediate contributions, such as an
increase in sales and profitability, rather than simply goodwill and its invisible
long-term impact. However, as mentioned previously, the effects of public
relations on market performance have been explored by examining the
relationship between the outcome measure of public relations (e.g., goodwill,
reputation) and economic performance. Only a few studies have tried to show the
contribution of pubic relations to the company in terms of economic performance
by investigating the relationship between public relations expenditures and market
performance (Kim, 1996, 2001). Balasubramanian and Kumar (1990) established
a model for estimating the relationship between marketing communication
intensity and market share. They found that the market share had a positive effect
in the consumer and industrial market but a negative effect in the service market.
Furthermore, in most prior studies that have investigated the direct effect
of public relations on market performance, the contribution of public relations
was examined through economic modeling, including public relations
expenditures. However, when examining the simultaneous effect of advertising
and public relations, measuring public relations in terms of monetary value might
be problematic because it is realistically difficult to distinguish advertising
40
expenditures from public relations expenditures. Details are mentioned in the
methodology section. Very little research has explored the contribution of public
relations in terms of publicity. Carroll and McCombs (2003) emphasized the
importance of the media coverage effect and suggested that companies making
themselves prominent on the media agenda are more likely to be prominent on the
pubic agenda, whereas those companies not on the media agenda are far less
likely to be prominent in the public’s mind. This study assumes that the
prominence of a company on the public agenda, in turn, is linked to a firm’s
business performance.
The present study defines publicity as the most representative public
relations activity and examines the effect of publicity on market performance.
Market performance is represented by sales revenue, which is the most direct
measure. The hypothesis regarding this relationship was established.
Hypothesis 4: Favorable publicity will have a positive impact on sales
revenue.
In summary, this chapter provides two research questions and four
hypotheses. The first research question examines the relationship between
advertising, publicity, and corporate reputation. The second research question
41
explores the impact of advertising and publicity on sales revenues. To answer
these two research questions, four hypotheses were suggested. All positive
relationships were expected regarding the four hypotheses: the positive
advertising-corporate reputation relationship, the positive publicity-corporate
reputation relationship, the positive advertising-sales relationship, and the positive
publicity-sales relationship.
42
CHAPTER 4
METHODOLOGY
Data and Sample
This study is basically an analysis of secondary data to provide the most
comprehensive analysis of the relationships between advertising, public relations,
corporate reputation, and market performance. Data on the advertising
expenditures, publicity index, corporate reputation, sales revenue, and other firm
variables were obtained from multiple sources: COMPUSTAT database,
Fortune’s America’s Most Admired Companies Survey, and the online news
database Lexis-Nexis.
To identify the sample of firms to be included in the study, all the firms
included in Fortune’s America’s Most Admired Companies survey from 1985 to
2005 were searched. The following criteria were established for a firm to be
included in the sample. First, the firm must have a reputation rating for each year
in the 21-year period from 1985 through 2005. Second, the firm’s financial and
industry data must be available from the COMPUSTAT database for each year
from 1985-2005. Based on these criteria, this study eliminated firms in the dataset
when they did not report information on their advertising expenditures, sales, and
43
other market/financial performance outcomes in the COMPUSTAT database from
1985 to 2005. These criteria did not allow this study to include all firms of
Fortune’s America’s Most Admired Companies survey. A great number of the
firms included in Fortune’s American’s Most Admired Companies survey did not
meet these criteria and thus were not included in the study. After searching
different sources, the present author obtained complete data on 18 companies.
Then, to calculate the publicity index of each company, all news stories about the
18 companies from 1985 to 2005 were collected using the online news database
Lexis-Nexis. Table 1 presents the 18 companies used in this study and their
industry/product type.
44
Table 1
Companies Used in the Study
Industry Type a
Company
Product Type b
American Standard
Industrial and farm equipment
Consumer/Industrial
Apple Computer
Computers
Consumer
AT&T
Telecommunications
Consumer/Industrial
Coca Cola
Beverages
Consumer
Delta Air Lines
Airlines
Consumer
Fortune Brands
Home equipment, furnishing
Industrial
Gillette
Household and personal product
Consumer
Johnson & Johnson
Pharmaceuticals
Consumer
Kimberly Clark
Household and personal product
Consumer
Pfizer
Pharmaceuticals
Consumer
PPG Industries
Chemicals
Industrial
Procter & Gamble
Household and personal product
Consumer
Sara Lee
Consumer Food Products
Consumer
Stanley Works
Household and personal product
Consumer/Industrial
Texas Instruments
Semiconductors
Industrial
United States Tobacco
Inc.
Tobacco
Consumer
VF Corp.
Apparel
Consumer
Vulcan Materials
Building materials, glass
Industrial
a
Industry type was classified based on industry category provided by Fortune. For a 21-year
period (1985-2005), certain companies have not been in the same industry category. For
example, in 1989, Texas Instruments was in “Electronics” industry but in 2005 it was the leader
of “Semiconductors” industry. Industry type, thus, was based on the information from the
companies as of 2005. Industry type was categorized into product firms and service firms.
b
Product type was categorized based on 10-k reports provided with SEC (Securities and Exchange
Commission). All publicly traded companies must file 10-k reports with the SEC. A 10-k report
includes a section describing a firm’s business and its largest markets. The SEC provides the
45
reports in its Edgar files on the Internet. As a result, product type was categorized into customer
products, industrial products, and both customer and industrial products.
Note: On the basis of the industry and product type, the sample of this study is divided into 4
categories: 10 consumer products firms, 4 industrial products firms, 2 firms with both consumer
and industrial products, and 2 services firms.
Measurements of Variables
The major goal of this study is to analyze the effect of marketing
communication on corporate reputation and sales revenue. Specifically, the first
objective of this study is to examine the effect of marketing communication
efforts (advertising and publicity) on corporate reputation. For examining the
relationship between marketing communication and corporate reputation, this
study controlled for dividend policy, diversification, market performance (marketto-book ratio), and profitability (return on investment capital: RIOC) that prior
literature has shown to be associated with corporate reputation. Firm size, which
may affect a firm’s reputation, was also included as an additional control variable.
The second objective of this study is to provide an analysis of the
relationship between marketing communication and sales revenues. For analyzing
the impact of advertising and publicity on sales revenue, R&D expenditure and
focus of the firm, which have been found to affect brand or company market
performance studies, were included. Also, firm size and corporate reputation were
46
included in the model to analyze the relationship between marketing
communication and sales revenue.
As indicated above, in order to analyze these relationships, this study has
two sets of variables. Figures 1 and 2 present frameworks for addressing the effect
of marketing communication on corporate reputation and sales revenue. All
variables described in Figures 1 and 2 were categorized into variables related to
the marketing communication, account/finance, strategy, and firm characteristics.
Figure 1
Framework for Analysis - Corporate Reputation
47
Figure 2
Framework for Analysis - Sales Revenue
Detailed discussions about each variable are listed as follows:
Independent Variables
Advertising
Advertising is measured as a firm’s total advertising expenditure for the
year. While there is disagreement regarding the definition and measurement of
advertising, most quantitative research investigating the relationship between
48
advertising and market performance has traditionally measured advertising in
terms of annual expenditures (Balasubramaniana and Kumar, 1990; Ailawadi,
Farris, and Parry, 1994; Zinkhan and Cheng, 1994; Herremans et. al., 2000; Yoo
and Mandhachitara., 2003; Ailawadi et. al., 2003; Mizik and Jacobson, 2003;
Fombrun and Shanley, 1990; Graham and Frankenberger, 2000). To measure the
quantity of advertising, researchers typically assume that advertising dollar
expenditures capture alternative choices of media, psychological appeals, and
copy. Previous studies examining factors that influence corporate reputation have
also defined advertising as annual expenditures (Fombrun and Shalley, 1900;
Roberts, 2000; Acquaah, 2003). Therefore, this study measures advertising as
actual annual expenditures on advertising. Advertising expenditure data were
drawn from the COMPUSTAT database. This database provides annual
accounting information regularly reported by public firms to the Securities and
Exchange Commission (SEC).
A lagged effect of advertising on corporate reputation and sales revenues
was anticipated. Thus, in order to account for a carryover effect and preclude
reverse causality, this study used a lagged effect of a firm’s advertising (year t-1)
on its reputation and sales revenue in year t.
49
Publicity
Since advertising or marketing professionals and public relations or
journalism professionals all have different orientations and definitions of public
relations, realistically, it is very difficult to find a standardized measurement of
public relations. Although a few studies measure pubic relations in terms of
monetary value, such as annual expenditures on public relations activities (Kim
1997, 2002), the present study does not measure public relations in monetary
terms. This deserves further explanation. There are a few reasons why public
relations cannot be measured in terms of expenditures when simultaneously
exploring the effect of advertising and public relations. One important reason is
that there are no official PR expenditure data. While a few industry studies have
surveyed public relations expenditure [Thomas L. Harris/Impulse Research
Survey 1997; The AMA/Wayman Group Marketing Industry Report Miller 1996;
Nichol & Co.’s Importance of PR at Fortune 500 companies study by Proof
Positive 1998; the Conference Board’s Managing Corporate Communications in
Competitive Climate study by Troy 1993; and Corporate Contributions study by
Tillman 1996], most of them have measured public relations in terms of
expenditure ranges, rather than as exact figures. Moreover, those data are
typically kept confidential.
50
Also, even if a researcher gets public relations expenditure data from each
corporation, there is still a problem in representing public relations expenditures.
Generally, public relations expenditure data reported from a public relations
department in a company include corporate advertising expenditures. However,
most advertising data (e.g., Adage or COMPUSTAT database) have been reported
on the basis of total media expenditure, including both brand advertising and
corporate advertising expenditures. That is, there is some overlap in advertising
expenditure data and public relations expenditure data. It is impossible to separate
brand advertising expenditure and corporate advertising expenditure in the official
advertising expenditure data. Therefore, this might be problematic when one
attempts to simultaneously examine advertising and public relations effects in
terms of monetary value.
This fact is clearly evidenced in Hutton, Goodman, and Alexander’s
(2001) study and Kim’s (2001) study. For example, Kim (2001) described public
relations expenses as including eight categories: 1) media and press relations, 2)
employee communications, 3) local community relations, 4) federal and local
government affairs, 5) environmental and safety affairs, 6) investor relations, 7)
contributions, and 8) corporate advertising. This definition is similar to the one
used in the study by Hutton, Goodman, and Alexander (2001). They mentioned
that public relations expenditures consist of 1) corporate advertising, 2)
51
foundation fundings, 3) social responsibility (community relations, nonfoundation
fundings, etc), 4) government relations, 5) employee communications, 6) investor
relations, 7) department management, 8) corporate identity, 9) media relations,
10) annual/quarterly reports, 11) industry relations, and 12) executive outreach.
According to their study, corporate communication professionals reported that
corporate advertising occupied a great portion of PR expenditure. These studies
also indicate that the firms include different types of activities as public relations
expenditures.
Since this study simultaneously examines advertising and pubic relations
effects, public relations expenditures are not a good measure for this study.
Moreover, obtaining public relations expenditure data for a 21-year period is not
realistically feasible because of the absence of available public data.
Alternatively, public relations has been measured in terms of publicity in
prior studies. Many communication researchers refer to “source credibility”
theory when mentioning the effect of public relations. Recently, marketing-related
academic researchers and professionals have said that as traditional advertising
struggles to catch consumers’ attention, public relations has been recognized as a
vital marketing communication tool because of its credibility and reliability
(Economist, 2006, Ries and Ries, 1996).
52
The media provide positive or negative information about a firm to
various stakeholders. Since some stakeholders lack direct experience with a firm,
they rely on information provided by the media who screen, spin, and broker
information for stakeholders. According to Fombrun (1996) and McQuail (1985),
stakeholders believe that the media help them make sense of companies’ complex
activities, and as such, affect corporate reputation. The media report the
evaluations of other information intermediaries and provide a consolidated source
of information for stakeholders. The media is a counteracting institution that
reduces stakeholders’ uncertainty about a firm’s characteristics, which is
reputation’s signaling role (Akerloff, 1970; Fombrun and Shanley, 1990; Weigelt
and Camerer, 1988). Therefore, even though publicity may not represent the
whole spectrum of public relations activities, it is the most realistic measure of
public relations.
To obtain a firm’s publicity data for each year, content analysis was
conducted. This author determined that a newspaper is the best media source of
public knowledge and opinion about companies. Although a mention on the
evening television news is a strong signal about the salience of the company,
newspapers have a more salient effect in setting the agenda among the public than
does television news. The lead story on page one, front page versus inside page,
the size of the headline, and even the length of a story in newspapers all
53
communicate information about the salience of the company (Carroll and
McCombs, 2003). Moreover, audience recall is stronger from newspaper stories
(DeFleur, Davenport, Cronin, and DeFleur, 1992; Robinson and Levy, 1996).
Thus, publicity is defined as the extent of favorableness of news articles about a
firm written in newspapers during the year.
The selected sources are two major daily newspapers whose coverage
could be traced a 21 -year period: Wall Street Journal and The New York Times.
These two major newspapers frequently report on the day-to-day business news
and have been frequently used in many prior studies. Also, they were ranked in
second and third places on the top 10 daily newspapers in the United States as of
March 31, 2006 (The Audit Bureau Circulation).
The news presented about a firm can deal with all kinds of information
about a company including the CEO’s image, employee satisfaction, and work
conditions, etc., as well as product information. Therefore, the sample of news
articles included all letters to the editor, all editorials, all columns, and all other
news articles about the firm.
Data on news about a firm were collected from the online news database
Lexis-Nexis, using a keyword of the name of each company. As a result,
tremendous amounts of news stories about a firm for the 21- year period from
1985 to 2005 were found. For example, there were 78,984 news stories about
54
Johnson & Johnson for 21 years from 1985 through 2005. For AT&T, 17,854
news stories were found for a 21-year period from 1985 to 2005.
Thus, a random sample was employed for content analysis. Since there are
no universally accepted criteria for selecting the sample size, this study
determined the desired sample size using a generalized method. According to
McCombs and Poindexter (2000) and Neuendorf (2002), about 400 news reports
of each company are desirable at 95% level of confidence and ±5% sampling
error. For each company, therefore, approximately 400 news articles about a firm
from 1985 through 2005 were randomly selected using a systematic random
sample. That is, 19 news articles about a firm for each year were collected. For
companies with fewer than 400 articles in given years, all articles were selected to
increase accuracy. This sampling procedure yielded a total of 6,852 news stories
for all 18 companies.
The contents of each news story were analyzed and classified as indicating
favorable, unfavorable, or neutral news about a firm for each year. Two coders
read and coded the full contents of all articles. This study followed Deephouse’s
(2000) coding scheme to evaluate each news article. When a firm was praised for
its actions or associated with actions that increase a firm’s overall evaluation, it
was rated as “favorable.” An “unfavorable” occurred when a firm was criticized
for its actions or associated with actions that decrease a firm’s overall evaluation,
55
such as legal regulation, crises, federal investigations, law suits, layoffs, etc. A
“neutral” rating was the declarative reporting of performance without evaluation,
such as announcements concerning performance, new products, a new CEO, and
so forth. When there is a “mixed” evaluation – both favorable and unfavorable –
in a news article, a neutral rating was given. Even though a “mixed” and a
“neutral” rating are conceptually different, they were used interchangeably when
there was a balance of favorable and unfavorable reporting in a news article.
Each coder recoded the total number of articles, the number of favorable
articles, the number of unfavorable articles, and the number of neutral articles for
the year. Two coders indicated high intercoder reliability (95%)1. After the coding
was complete, the author coded a random sample of 100 articles as a subsample.
Coders and the author agreed on 97% of the codes. Generally, these coding
procedures enhance the reliability of the coding process.
Based on this classification, a favorable index of news for each year was
created using the Janis-Fadner coefficient of imbalance (Janis and Fadner, 1965,
Equation 1). This equation calculates the degree to which media reports were
positive. The Janis-Fadner (1965) coefficient of media favorability has been used
in strategy research involving media to assess the degree of media favorability
(Carroll, 2004; Deephouse, 2000; Pollock and Rindova, 2003). Initially developed
1 SPSS (Statistical Package for the Social Science) was used to calculate Cohen’s kappa. Cohen's kappa
measures the agreement between the evaluations of two raters when both are rating the same object.
56
for analyzing wartime propaganda, it measures the relative proportion of
favorable to unfavorable articles while controlling for the overall volume of
articles. In this study, this index was used as representing the publicity measure.
The formula to calculate publicity measure is as follows:
Publicity = (f2 – fu)/(total )2, if f > u
0,
if f = u
2
2
(fu – u )/(total ) , if f < u
[Equation 1]
where f = the number of favorable recording units in a given year; u = the number
of unfavorable recording units in that year; and total = the total number of
recording units in that year. The range of this variable is -1 to 1, where 1 indicates
all positive coverage, -1 indicates all unfavorable coverage, and 0 means a
balance between the two over the year.
As a result, 29.9% of the news articles were rated as unfavorable, 8.2%
were coded as neutral, and 61.9% were rated as generating favorable publicity.
Dependent Variables
Corporate Reputation
Reputation encompasses everything that is known about a firm. As an
empirical representation, it is a judgment of the firm made by a set of audiences
57
on the basis of perceptions and assessments that are assembled and made
available via the ranking system (Fombrun and Shanley, 1990). The ranking
system defines, assesses, and compares firms’ reputations according to certain
predefined criteria. In this study, corporate reputation is defined as a perceptual
representation of a company’s past actions and future prospects that describe the
firm’s overall appeal to all its stakeholders when compared to other leading rivals
(Roberts and Dowling, 2002; Weiss, Anderson, and MacInnis, 1999). That is,
reputation refers to a firm’s overall evaluation at the corporate level, rather than
brand level.
Typically, national lists of reputation are published annually by national
business magazines (e.g., Fortune, The Financial Times, The Far East Economic
Review, Asian Business and Management Today, etc.). One of the most wellknow reputation ranking systems is found in the annual Fortune survey of
America’s Most Admired Companies, which has been published by Fortune
Magazine since 1982. Fortune’s database provides information that can be used to
operationalize the corporate reputation activities of firms (Vergin and Qoronfleh,
1998). In this study, corporate reputation will be measured as Fortune’s
reputation index, derived from Fortune’s annual survey of America’s Most
Admired Companies.
58
Fortune has conducted surveys on large American firms since 1982 and
has published the results early each year since 1983. The magazine collects data
on the largest firms in over 30 industries. Fortune administers the surveys to over
8000 top executives and outside directors who are knowledgeable about the
industries in which their firms operate, and market analysts who evaluate firms in
these industries. Industry analysts and executives within an industry have been
shown to be reliable and accurate raters of corporate strategy (Chen, Fahr, and
MacMillan, 1993). They are asked to rank the companies based on their
effectiveness in performing the activities described by each of the eight attributes.
The eight attributes are
(1) quality of management,
(2) quality of products or services,
(3) innovativeness,
(4) ability to attract, develop, and keep talented people,
(5) wise use of corporate assets,
(6) responsibility to the community and environment,
(7) soundness of financial position, and
(8) value as a long-term investment.
59
Each company is rated relative to its leading competitors on eight
characteristics using an 11-point scale (0 = poor, 10 = excellent). Then, an index
of overall reputation from the eight single dimensions is made. That is, the
reputation rating is reported as an overall reputation index. The response rate has
averaged about 50% for each year of the survey. With this high response rate,
Fortune’s survey sample is probably larger than most samples obtained by
academic researchers, and its members are probably more qualified and better
informed (Brown 1994). The results have been widely circulated and cited in
popular press outlets. According to Dutton and Jackson (1987), if reputational
rankings are widely publicized (e.g., Fortune has have become), they may alter
managers’ perceptions of environmental threats and opportunities and of their
firms’ strengths and weaknesses and so influence the mobility barriers that
managers enact. That is, well-reputed firms have a competitive advantage within
their industries, but poorly reputed firms are at a disadvantage.
The Fortune data have been chosen to measure the corporate reputation
for several reasons in many previous studies. First, the eight attributes likely
represent the collective and collaborative capabilities of a firm’s corporate
management that are difficult for rivals to imitate and thus may be used to manage
and build a firm’s reputation and earn firm-specific profits. Second, the survey
offers data from a large sample of industry experts who have access to internal
60
firm and industry information about the qualitative dimensions of the firm’s
intangible resources and capabilities. It has been argued that the assessment of a
firm’s intangible resources and capabilities should not be an internal affair, but
should be done by external constituents who can objectively examine what the
firm does more effectively than its competitors (Collins and Montgomery, 1995).
According to Hammond and Slocum (1996), the quality of respondents of the
Fortune survey is comparable to those that could be obtained elsewhere since
respondents only rate firms with which they are familiar. In an exploratory study,
Chen et al. (1993) provide support for the reliability and accuracy of information
offered by top executives and market analysts. For these reasons, this study used
Fortune’s America’s Most Admired Companies data to measure corporate
reputation. The description of how America’s Most Admired Companies survey
was conducted in 2005 is presented in Appendix A.
Sales Revenue
Many previous studies have attempted to examine the impact of
advertising or public relations on market performance. In general, market
performance has been measured by either profitability or sales/revenue.
Profitability can be expressed in several ways, including return on investment
(ROI), return on sales (ROS), and return on equity (ROE) (Szymanski, Bharadwaj,
61
and Varadarajan, 1993). In this study, sales revenue was chosen for measuring the
company’s market performance impact because it is the most straightforward and
popular measure of market performance. The data on sales revenue were obtained
from COMPUSTAT database.
Other Variables
Other variables that have been shown to influence corporate reputation or
market performance measures were included. These control variables estimate the
net effects of marketing communication on corporate reputation and sales revenue.
The selection of these other variables is based on prior empirical studies. The
selection of these variables is also partly influenced by the availability of data.
Diversification
Although there are conflicting interpretations about diversification,
previous research has indicated that the capital markets favor firms that only
diversify into related product market domains to capitalize on synergy (Bettis,
1981; Rumelt, 1974). Reputation literature has noted that when firms diversify
into related product market, it enhances firm's reputation. Firms with unrelated
portfolios, for instance, may spirit cash away from profitable divisions instead of
reinvesting it in needed R&D (Hoskisson and Hitt, 1988), spend less on
62
advertising (Bettis, 1981), and carry a high percentage of debt (Barton and
Gordon 1988), all of which may harm a firm’s external image and increase its
perceived risk to investors.
Diversification was derived by using the COMPUSTAT database.
COMPUSTAT provides data on a firm’s annual sales by segment. From these
data, a continuous Herfindahl-type measure of diversification (Amit and Livnat,
1988) across segments at the end of fiscal year was created by using this equation,
1- (∑Salesj2)/(∑Salesj)2 ,
[Equation 2]
where j = the number of segments.
Montgomery (1982) indicated that firms with low diversification tended to
be more focused and that firms with high diversification were involved in a broad
range of business. The diversification measure is highly correlated with Rumelt’s
(1974) categorical measure of relatedness, suggesting that firms with high scores
on the index are more likely to encompass less related business under their
corporate umbrellas than firms with low scores on the index. The reputation
literature has noted that diversification tends to negatively influence corporate
reputation (Fombrun and Shanley, 1990).
63
This study accounted for the effect of a firm’s diversification in period t-1
on corporate reputation in period t in accordance with Fombrun and Shanley
(1990)’s conceptual framework of reputation building.
Market-to-Book Ratio
Just as price signals product quality, high economic performance signals a
firm’s inherent quality to its constituents. That is, high performance makes
constituents assess firms favorably. The market-to-book ratio is a good indicator
to measure a firm’s financial value. The market-to-book value relates the firm’s
market value per share to its book value per share. The market-to-book ratio is
calculated by dividing price per share by book value per share. Book value per
share can be calculated by dividing total owner’s equity by the number of shares
outstanding (Copeland, Keller, and Murrin, 1994). That is, the general definition
of the market-to-book ratio is as follows:
M/B Ratio = price per share/(total owners’ equity/number of shares
outstanding)
[Equation 3]
A market-to-book ratio of 1.0 means that the market value of a firm is
equal to its book value. A market-to-book ratio greater than 1.0 means that the
64
market value is higher than the book value and suggests that a firm has intangible
assets which are not recognized by current accounting practices. A market-tobook ratio less than 1.0 means that the book value of a firm is higher than the
market value of a firm. It indicates that a firm does not have intangible assets
exceeding tangible assets.
Market-to-book ratio is an important control variable in this model. The
measure of reputation used in this study is based on the perceptions of senior
company managers and directors, as well as associated industry analysts
(Fortune’s reputation index). While the use of a perceptual measure of reputation
poses no problems per se (Benjamin and Podolny, 1999; Dowling, 2001), there
may be concern about the financial orientation of these respondents. One might
suspect that the reputation scores that are reported are confounded by the
respondents’ expectations of the firms’ future financial performance. In other
words, higher reputation scores may be given to firms that are expected to
perform well in future years. Inclusion of the market-to-book value variable eases
this concern because it captures the market’s expectation of future economic
returns (Muller, 1990). The market-to-book ratio was calculated using Equation 3.
Data needed for Equation 3 are derived from the COMPUSTAT database.
65
Accounting Profitability
Accounting profitability measured as return on investment capital (ROIC)
is another indicator to represent a firm’s economic performance. ROIC is a
calculation used to determine the quality of a company. The general definition for
ROIC is as follows:
Return on Investment Capital = (net income-dividends)/total Capital
[Equation 4]
Total capital includes long term debts, preferred stock, and common
equity. This is always calculated as a percent. Accounting profitability was
calculated using Equation 4. Data for Equation 4 are from the COMPUSTAT
database. As with diversification, the effect of the prior year’s accounting
profitability on the current year’s corporate reputation was considered based on
prior research (Fombrun and Shanley, 1990).
Dividend Yield
Dividend policy is also an aspect of economic performance. High
distribution may be interpreted as indicating that a firm is more profitable than
competitors, but it may be regarded as a signal that the firm lacks attractive
66
investment opportunities capable of ensuring future cash flow (Ross, 1977). These
expectations also influence the stock price of the firm. Therefore, the dividend
yield (a ratio of dividend payout to stock price, [Equation 5]) is a useful indicator
of the public’s view of firms. Ross and Westfield (1988) suggested that firms with
high growth prospects will generally have lower dividend yields. Prior studies
expected a negative association between dividend yield and reputation. For
example, Fombrun and Shanley (1990) suggested that when publics assess the
reputational status of the firm, the greater a firm’s current dividend yield, the
worse its reputation. The COMPUSTAT database provides a firm’s dividend
yield for each year.
Company Size
Large firms tend to receive a great deal of public scrutiny and attention.
The availability of information may benefit large firms by inflating audiences’
familiarity with their activities (Tversky and Kahneman, 1974). Therefore, a
larger company is believed to have a more favorable corporate reputation
(Fombrun and Shaley, 1990). Also, firm size has been employed as a control
variable to estimate market performance (Deephouse, 2000). Thus, it is
reasonable to expect that firm size will influence corporate reputation and sales
revenue.
67
In this study, firm size was measured using the annual number of
employees in accordance with previous studies (Bharadwaj et al., 1999; Nickell,
1996; Acquaah, 2003). Data on the number of employees were obtained from the
COMPUSTAT database.
Research & Development
There is a large body of finance, management, and marketing research that
relates the intangible assets created by research and development (R&D) to the
firm’s market and financial performance. Although there is a debate about the size
of the effects of R&D investments of different performance metrics (Boulding
and Staelin, 1995; Erickson and Jacobson, 1992), it is well-established that firms’
R&D investments generate persistent profits (Roberts, 2001) and superior market
value (Jaffe, 1986). In a meta-analysis of 210 profitability studies, Capon, Farley
and Hoeing (1990) concluded “dollars spent on R&D have an especially strong
relationship to increased profitability.”
R&D leads to greater cash flow and increases firms’ market value. For
example, intense R&D can ensure speedy and successful commercialization of
technologies and products at a low cost (Dutta, Narasimhan, and Rajiv, 1999).
Thus, higher R&D investment may lead to greater speed and levels of cash flow,
along with lower vulnerability and volatility, which can promote greater market
68
value in the long run (Griffin and Hauser, 1996; Srivastava, Shervani, and Fahey,
1999). Also, from the resource-based-view (RBV) perspective, marketing and
R&D have been recognized as performance-enhancing instruments. R&D
expenditures of each firm were derived from the COMPUSTAT data set.
In order to account for a carryover effect and preclude reverse causality,
this study used a lagged effect of a firm’s R&D (year t-1) on its sales revenue
(year t).
Focus of the Firm
Focus of the firm was measured by the number of industry segments in
which the firm operates (Rao, Agarwal, and Dahlhoff, 2004; Luo and Donthu,
2006). Focus of the firm is related to diversification. According to Montgomery
(1982), firms with low diversification tended to be more focused and firms with
high diversification were involved in a broad range of business. In prior studies,
interpretations about the relationship between the focus of the firm and market
value are conflicting. Thus, this study has no prior expectation of this relationship.
COMPUSTAT provides data on a firm’s annual sales by segment. From this data,
the number of industry segments of a firm was counted.
69
Corporate Reputation
Literature dealing with the relationship between reputation and market
performance is well-established. Many empirical studies have found that a
favorable reputation positively affects a firm’s performance (Brown 1998;
Deephouse, 2000; Fombrun, 1996; Kotha et al., 2001; McMillan and Joshi, 1997;
Roberts and Dowling 2002). In general, brands with a good reputation are posited
to be high in sales since these brands enjoy greater perceptual enhancement. Such
superior value is also viewed in the marketing literature as leading to greater
market share and profits for the company (Day and Wensley, 1998). Thus, the
positive reputation of the brand or/and company leads to greater company
profitability.
There is a great deal of evidence to support the idea that corporate
reputation contributes to the market performance. Traditionally, although a lack of
a widely accepted measure of reputation has caused difficulty in creating wellreasoned and defensible answers about corporate reputation and reputational
dynamics, marketing literature suggests that a good reputation supports and
enhances sales force effectiveness (Dowling, 2001). Recently, formal research has
outlined some of the strategic planning implications behind corporate reputation
(Fombrun and Van Riel, 1997). For example, Hammond, Annis, and Slocum
(1996) found that corporate reputation is linked with a firm’s bottom line financial
70
performance. According to their findings, investors may consider less socially
responsible organizations riskier investments because of possible governmental
intervention. If a firm is viewed as socially responsible, it may have a relatively
low financial risk as a result of its strong relationship with the surrounding
community. Roberts and Dowling (2002) found that a good reputation at a given
point in time allows superior financial performance to persist by examining the
relationship between reputation and the persistence of superior profit outcomes
over time. Kim (1997, 2001) found a positive relationship between a company’s
reputation and financial returns and revenues.
Reputation was measured as Fortune’s reputation index. A lagged effect
of reputation on sales revenue was anticipated. Thus, the effect of reputation in
year t-1 on sales revenue in year t was examined.
All data included in this study – advertising expenditures, publicity,
corporate reputation, sales revenue, and other variables such as dividend policy,
diversification, market-to-book ratio, profitability, R&D, focus of the firm and
firm size – are the firm level data. Details on measures of variables are
summarized in Table 2.
71
Table 2
Summary of Measures and Data Sources
Variables
Definition
Measures
Total Advertising Expenditure
of the year
Data Source
Advertising expenditure
COMPUSTAT
The Extent to Which the News
Articles are Positive about a
Company
Corporate reputation based on
an annual survey of the most
admired U.S. corporations
(f2 – u)/(total )2, if f > u
0, if f = u
(fu – u2)/(total )2, if f < u
Lexis-Nexis
Fortune Reputation index
Fortune
Sales Revenue
Net Sales of the year
Sales
COMPUSTAT
Diversification
Business relatedness measure
1- (∑Salesj2)/(∑Salesj)2
COMPUSTAT
M/B ratio
The market value of a firm
dividend by capital invested
price per share/(total
owners’ equity/number of
shares outstanding)
COMPUSTAT
Profit
Return on investment capital
(ROIC)
(net incomedividends)/total capital
COMPUSTAT
Dividend Yield
The yield a company pays out
to its shareholders in the form
of dividends
Dividend payout/stock
price
COMPUSTAT
R&D
Total R&D expenditure of the
year
R&D expenditure
COMPUSTAT
Focus of the
Firm
The number of industry
segments the firm operates of
the year
The number of industry
segments
COMPUSTAT
Firm Size
Number of employees
The annual number of
employees
COMPUSTAT
Advertising
Publicity
Corporate
Reputation
72
CHAPTER 5
ANALYSES AND RESULTS
This study examines the impact of a firm’s advertising and publicity on
corporate reputation and sales revenue. The underlying argument of the
hypotheses regarding the effect of marketing communication on corporate
reputation and market performance is that firms with high levels of advertising
and favorable publicity generate much higher corporate reputation assessments
and sales revenues. To assess the effects of these two important marketing
communication activities – advertising and publicity – two sets of analyses were
carried out: descriptive analysis and time-series analysis.
First, in order to address whether firms with high advertising and
favorable publicity build much higher corporate reputations and sales revenues,
this study conducted a descriptive analysis. Rather than providing simple
correlations, mean values, and standard deviations of each variable, the present
study compares the mean values of corporate reputation for firms with high versus
low advertising and favorable versus unfavorable publicity. For the purpose of
comparison, firms were classified as high or low in advertising expenditure and
favorable or unfavorable in publicity using a median split. Then, simple
interaction effects of advertising and publicity on corporate reputation were
73
addressed. The effects of the level of advertising and the valence of publicity on
sales revenues were also examined in the same way.
For overall descriptive analyses, time-series data were dealt with as crosssectional data. A total of 378 firm-year observations for 18 companies had
complete data on advertising, publicity, corporate reputation, and sales revenue
from 1985 through 2005.
Second, after addressing the descriptive analysis, hypotheses testing was
done. For testing hypotheses, a time-series analysis was conducted. Since
longitudinal time-series data displayed auto-correlative properties, autoregressive
(AUTOREG) procedure in SAS was employed. For a time-series analysis, 21year data of 18 companies from 1985 to 2005 were used. More details on timeseries analysis are presented in the hypotheses test. Hypotheses test results
followed the descriptive analyses.
Descriptive Data Analysis
Prior to testing the hypotheses, a few descriptive analyses were conducted
using cross-sectional data of 378 firm-year observations for 18 companies. This is
to assess the implicit argument of this study that firms with high levels of
74
advertising and favorable publicity generate higher corporate reputations and
sales revenues.
Next, this section describes the relationship between publicity and
corporate reputation and the relationship between publicity and sales revenue.
Then, it presents the relationship between three different measures of advertising
and corporate reputation and the relationship between three different measures of
advertising and sales revenue. Finally, simple results of the interaction effect of
advertising and publicity on corporate reputation and the interaction effect of the
two marketing communication variables on sales revenue are provided.
Publicity and Corporate Reputation
The question of whether favorable or unfavorable publicity made any
difference in corporate reputation is examined. As discussed previously in the
section on measures of variables, the Janis-Fadner coefficient of imbalance
[Equation 1] yields the index of news favorability, publicity. The range of this
variable is -1 to 1, where -1 indicates all unfavorable coverage, 1 indicates all
favorable coverage, and 0 means a balance between the two over the year. For
example, if a firm had -0.89 in this variable, it means that unfavorable publicity
was dominant for the firm over the year.
75
In order to see the difference between favorable and unfavorable publicity,
the publicity variable was recoded into two categories (favorable and unfavorable
publicity). When a firm had a minus number in the publicity variable, it was
recoded as “-1,” indicating that unfavorable publicity was predominant over the
year. In contrast, the firm was recoded as “1” when publicity variable showed a
plus number, suggesting that favorable publicity was dominant over the year.
Here, the neutral publicity indicated as “0” in Janis-Fadner coefficient was
eliminated to compare the distinct effects of favorable and unfavorable publicity
on corporate reputation. As a result, a total of 31 of 378 observations (8.2%) were
excluded.
This study explored the effects of favorable and unfavorable publicity on
corporate reputation, using cross-sectional time series data of 378 firm-year
observations for 18 companies. Overall, for the 18 companies, favorable and
unfavorable publicity exhibited a different effect on corporate reputation: firms
with favorable publicity (mean= 7.08, S.D. = .89) vs. firms with unfavorable
publicity (mean = 6.53, S.D. = 1.04). This difference was statistically significant
(t = -5.075, p < .0001). That is, firms with favorable publicity exhibited a much
higher corporate reputation. Figure 3 shows the visual illustration of the overall
18 companies.
76
Figure 3
Mean Value of Corporate Reputation for Firms with Unfavorable and Favorable Publicity
7.2
7.1
7
6.9
6.8
6.7
6.6
6.5
6.4
6.3
6.2
Unfavorable Publicity
Favorable Publicity
Publicity and Sales
The descriptive analysis of publicity and sales was done in the same
manner as corporate reputation. The publicity variable was divided into two
categories (favorable and unfavorable) to see if there was any difference in sales
revenue depending on unfavorable and favorable publicity.
In addition to the absolute sales, the effect of publicity on changes in sales
revenue was examined. Change data can detect how the type of publicity is
related to changes in sales revenue. Changes in sales were obtained from original
77
data by subtracting sales dollars in year t-1 from sales dollars in year t (Sales t –
Sales t-1) [Equation 6]. If a firm’s sales of the year (t) were less than those of the
previous year (t-1), changes in sales could be negative numbers.
Unlike publicity and corporate reputation, favorable and unfavorable
publicity showed no effect on absolute sales revenue (firms with unfavorable
publicity, mean = 13016, S.D. = 13495.10; firms with favorable publicity, mean =
13714, S.D. = 15263.92, t = -.432, n.s.). As indicated in Figure 4, however,
changes in sales were different depending on the type of publicity, and the
difference was statistically significant (firms with unfavorable publicity, mean = 342.22, S. D. = 5734.90; firms with favorable publicity, mean = 731.91, S.D. =
3137.25, t = -2.244, p < .05). In other words, when favorable publicity was
dominant, firm sales increased compared with the previous year. In contrast, firm
sales decreased when unfavorable publicity was widespread.
78
Figure 4
Mean Value of Changes in Sales for Firms with Unfavorable and Favorable Publicity
800
600
mm $
400
200
0
Unfavorable Publicity
Favorable Publicity
-200
-400
Advertising and Corporate Reputation
In this descriptive analysis, the effect of advertising as a vital component
in the process of creating a firm’s value was measured in three ways: absolute
advertising expenditures, changes in advertising expenditures, and advertising
intensity.
The advertising effect might be different for these three different measures
of advertising. Absolute advertising expenditures were the total advertising
expenditures of year t. Changes in advertising expenditures were obtained the
same way that changes in sales were obtained. That is, changes in advertising
expenditures were obtained from original data by subtracting advertising
79
expenditure in year t-1 from advertising expenditure in year t (AD t – AD t-1)
[Equation 7]. Change data can provide a perspective on the marginal effect of
advertising. Lastly, advertising intensity was measured as the ratio of advertising
expenditures to total assets for each firm-year observation (advertising
expenditure/total assets) [Equation 8], which were also derived from the
COMPUSTAT database.
Total advertising expenditures and advertising intensity were recoded into
two categories using median splits. That is, they were divided into two categories
based on their median value of advertising expenditures and of advertising
intensity, respectively: low advertising vs. high advertising; low advertising
intensity vs. high advertising intensity.
Changes in advertising expenditures were recoded into two categories
based on the direction of the changes: negative changes in advertising
expenditures and positive changes in advertising expenditures. When a firm spent
more on advertising in year t than in year t-1, change data of advertising
expenditures could be a positive number. If a firm’s advertising expenditures were
less than those of the previous year, changes in advertising could be a negative
number.
80
Advertising Expenditures and Corporate Reputation
Absolute advertising expenditures were split by their median value
(253.30) into two categories: low advertising expenditures and high advertising
expenditures. As shown in Figure 5, firms with high advertising expenditures had
higher corporate reputation scores than firms that spent less on advertising. The
difference was statistically significant (firms with low advertising expenditures,
mean = 6.47, S.D. = .8717; firms with high advertising expenditures, mean = 7.23,
S.D. = 8808, t = -8.411, p < .0001). Figure 5 presents the mean values of
corporate reputation for firms with low and high advertising expenditures.
Figure 5
Mean Value of Corporate Reputation for Firms with Low and High Ad Expenditures
7.4
7.2
7
6.8
6.6
6.4
6.2
6
Low Ad Expenditures
High Ad Expenditures
81
Changes in Advertising Expenditures and Corporate Reputation
Next, the relationship between changes in advertising expenditures and
corporate reputation was examined. Changes in advertising expenditures were
obtained from original data by subtracting advertising expenditures in year t-1
from advertising expenditures in year t (Advertising Expenditures t – Advertising
Expenditures t-1). Then, advertising change data were categorized into two groups
based on whether their changes increased or decreased, compared with the
previous year: negative changes in advertising expenditures and positive changes
in advertising expenditures.
The result found that corporate reputation differed depending on changes
in advertising expenditures, and the difference was statistically significant (firms
with negative changes in advertising expenditures, mean = 6.61, S.D. = .9036;
firms with positive changes in advertising expenditures, mean = 7.00, S.D.
= .9536, t = -3.923, p < .0001). That is, when a firm spent more on advertising
compared with the previous year, the firm had a higher reputation score. In
contrast, corporate reputation decreased when a firm spent less on advertising
than the previous year. Figure 6 showed the difference in corporate reputation for
firms with negative changes in advertising expenditures and positive changes in
advertising expenditures.
82
These effects of advertising expenditures and changes in advertising
expenditures, however, could be attributed to the previous year’s sales revenues,
since advertising expenditures are decided based on previous year’s sales
revenues, the ratio of advertising to sales. In many cases, there may be no doubt
that sales revenue influence advertising expenditures. That is, higher reputation
scores for a firm with positive changes in advertising expenditures could be
attributed to higher sales revenues of the previous year. In the following section,
thus, advertising intensity was examined to rule out this alternative explanation
that the positive relationship between advertising and corporate reputation may be
due to larger firms having higher sales revenue.
83
Figure 6
Mean Value of Corporate Reputation for Firms with Negative and Positive
Changes in Ad Expenditures
7.1
7
6.9
6.8
6.7
6.6
6.5
6.4
Negative Changes in Ad Expenditures
Positive Changes in Ad Expenditures
Advertising Intensity and Corporate Reputation
Advertising intensity was measured as the ratio of advertising spending to
total assets for each firm-year observation (advertising expenditure/total assets).
Simply put, advertising intensity is used as a term controlling for a firm’s size
effect. Then, advertising intensity was recoded into two categories using median
split (median value = 0.0338): low advertising intensity and high advertising
intensity.
As in the case of advertising expenditures and changes in advertising
expenditures, advertising intensity was also related to corporate reputation. That is,
firms with high advertising intensity had higher corporate reputation scores than
84
firms with lower level of advertising intensity. The difference was statistically
significant (firms with low advertising intensity, mean = 6.49, S.D. = .8932; firms
with high advertising intensity, mean = 7.26, S.D. = .8724, t = -8.132, p < .0001).
This finding suggests that firms that have higher advertising expenditures are
more likely to generate favorable assessments of corporate reputation, regardless
of the firm size. That is, a firm’s size did not influence the positive relationship
between advertising expenditures and corporate reputation. Figure 7 presents the
mean values of corporate reputation for firms with low and high advertising
intensity.
Figure 7
Mean Value of Corporate Reputation for Firms with Low and High Advertising Intensity
7.4
7.2
7
6.8
6.6
6.4
6.2
6
Low Advertising Intensity
High Advertising Intensity
85
Advertising and Sales
Advertising Expenditures and Sales
Firms with higher advertising expenditures generated much higher sales
revenues than firms that spent less on advertising, and this difference is
statistically significant (firms with low advertising expenditures, mean = 5384.86,
S.D. = 3840.48; firms with high advertising expenditures, mean = 19231.45, S.D.
= 17005.76, t = -11.145, p < .0001). Figure 8 indicates the result of advertising
expenditures and sales.
Figure 8
Mean Value of Sales for Firms with Low Advertising Expenditures
and High Advertising Expenditures
25000
mm $
20000
15000
10000
5000
0
Low Ad Expenditures
High Ad Expenditures
86
Changes in Advertising Expenditures and Sales
When firms spent more on advertising than they did the previous year,
many companies (62%) generated sales increase. However, whether firms spent
less or more on advertising compared with the previous year did not show any
relevance with absolute sales revenues (firms with negative changes in advertising
expenditures, mean = 11567.81, S.D.= 14125.93; firms with positive changes in
advertising expenditures, mean = 13105.95, S.D. = 14481.44, t = -.941, n.s.).
Advertising Intensity and Sales
As seen in the advertising expenditures and sales relationship, firms that
spent more on advertising expenditures generated much more sales revenue than
firms with low advertising expenditures. However, there might be alternative
explanations for this relationship. As discussed in the section about advertising
and corporate reputation, one alternative explanation is that the positive
relationship between advertising and sales revenue may be due to larger firms
having higher sales revenue. Therefore, in this section, advertising intensity was
examined to eliminate this alternative explanation.
Unlike the relationship between advertising expenditures and sales,
advertising intensity was not associated with sales revenue (firms with low
advertising intensity, mean = 12501.33 S.D. = 16641.19; firms with high
87
advertising intensity, mean = 13772.11, S.D. = 11388.80, t = -.855, n.s.). High
advertising intensity did not increase a firm’s sales revenues. In other words,
when firm size was controlled for, the positive relationship between advertising
expenditure and sales revenue was not found. Thus, we can assume that the
positive relationship between advertising expenditures and sales revenues might
be attributed to the alternative explanation discussed previously – the positive
relationship between advertising and sales revenue may be due to larger firms
having higher sales revenue.
Interaction of Advertising and Publicity on Corporate Reputation
This section presents some simple results from a bivariate categorical
analysis of the interaction effect of advertising and publicity on corporate
reputation. As shown in Figures 9, 10, and 11, the interactions for three different
measures of advertising and publicity on corporate reputation are rather similar.
They show that firms with high levels of advertising and favorable publicity
generate higher corporate reputations than do firms with low advertising and
unfavorable publicity, respectively. The interaction effect of advertising and
publicity on corporate reputation was not clear. Figures show that there is no
difference in advertising effect between unfavorable publicity and favorable
88
publicity. That is, regardless of the amount of advertising, favorable publicity
generated much higher corporate reputations.
Specifically, as shown in Figure 9, firms with high advertising expenditure
and favorable publicity appear to build the highest corporate reputation (e.g., low
advertising and unfavorable publicity, mean = 6.20; low advertising and favorable
publicity, mean = 6.62; high advertising and unfavorable publicity, mean = 6.87;
high advertising and favorable publicity, mean = 7.40). In two different
advertising measures – changes in advertising expenditure and advertising
intensity – the results were similar. For changes in advertising expenditure, as
indicated in Figure 10, positive changes in advertising expenditures and favorable
publicity were the most effective in generating favorable assessments of corporate
reputation (firms with negative changes in advertising expenditure and
unfavorable publicity, mean = 6.31; firms with negative changes in advertising
expenditure and favorable publicity, mean = 6.74; firms with positive changes in
advertising expenditure and unfavorable publicity, mean = 6.64; firms with
positive changes in advertising and favorable publicity, mean = 7.19). For
advertising intensity, As seen in Figure 11, high advertising intensity and
favorable publicity were also good for favorable judgments of corporate
reputation (firms with low advertising intensity and unfavorable publicity, mean =
6.29; firms with low advertising intensity and favorable publicity, mean = 6.69;
89
firms with high advertising intensity and unfavorable publicity, mean = 6.96;
firms with high advertising intensity and favorable publicity, mean = 7.52).
Figure 9
Interaction Effect of Advertising Expenditures and Publicity on Corporate Reputation
7.6
7.4
7.2
7
6.8
6.6
6.4
6.2
6
Low Ad Expenditure
High Ad Expenditure
Unfavorable Publicity
90
Favorable Publicity
Figure 10
Interaction Effect of Changes in Advertising Expenditures and Publicity on Corporate
Reputation
7.4
7.2
7
6.8
6.6
6.4
6.2
6
Negative Changes in Ad
Positive Changes in Ad
Unfavorable Publicity
Favorable Publicity
Figure 11
Interaction Effect of Advertising Intensity and Publicity on Corporate Reputation
7.6
7.4
7.2
7
6.8
6.6
6.4
6.2
6
Low Ad Intensity
High Ad Intensity
Unfavorable Publicity
91
Favorable Publicity
Interaction of Advertising and Publicity on Sales Revenues
With respect to sales revenues, the interaction effect of advertising and
publicity illustrates interesting results. In both low and high advertising
expenditures, unfavorable publicity, rather than favorable publicity, was more
effective for generating higher sales revenues. However, the differences in sales
revenues made by the type of publicity in both low and high advertising
expenditures were not big (in low advertising expenditures, sales mean for
unfavorable publicity = 6230 vs. sales mean for favorable publicity = 5635; in
high advertising expenditures, sales mean for unfavorable publicity = 19923 vs.
sales mean for favorable publicity = 19318). This result appears in Figure 12A.
Rather, as shown in Figure 12 B, advertising appears to contribute more to
making a difference in sales revenues. It shows that the differences in sales
revenues made by advertising in both unfavorable and favorable publicity were
much bigger than those made by the type of publicity (Figure 12A vs. Figure
12B). This result does not imply that advertising is a more effective marketing
communication tool than publicity in increasing sales revenue. However, it
suggests that if the publicity condition is the same (unfavorable publicity or
favorable publicity), firms that spend more on advertising (high advertising
expenditures) generate much higher sales revenues: in unfavorable publicity, sales
92
mean for low advertising expenditure = 6230 vs. sales mean for high advertising
expenditure = 19,923; in favorable publicity, sales mean for low advertising
expenditure = 5635 vs. sales mean for high advertising expenditure = 19,318).
Figures 12A and B illustrate the different effects.
Figure 12
A: Interaction Effect of Advertising Expenditures and Publicity on Sales
25000
mm $
20000
15000
10000
5000
0
Low Ad Expenditurea
High Ad Expenditures
Unfavorable Publicity
93
Favorable Publicity
B: Interaction Effect of Advertising Expenditures and Publicity on Sales
25000
mm $
20000
15000
10000
5000
0
Unfavorable Publicity
Low Ad Expenditurea
Favorable Publicity
High Ad Expenditures
Advertising change data also show interesting results (Figure 13). When
firms spent less on advertising compared with the previous year (negative changes
in advertising expenditures), unfavorable publicity generated much higher sales
revenues, whereas in the positive changes in advertising expenditures, favorable
publicity yielded much higher sales revenues. Figure 13 indicates that even
though firms spent more on advertising compared with the previous year, if
unfavorable publicity was predominant, sales revenues decreased. The results of
this study are consistent with the results found in a prior study. In the late 1990s,
AT&T conducted a series of studies to better understand how advertising and
news coverage generated by public relations were combined to impact consumer
94
attitudes and perceptions. AT&T’s study found that when news coverage was
more positive than negative, incremental advertising had a positive impact on
attitudes, and that in instances of negative news coverage, incremental advertising
did not have a positive impact.
Figure 13
Interaction Effect of Changes in Advertising Expenditures and Publicity on Sales
14500
14000
mm $
13500
13000
12500
12000
11500
11000
Negative changes in ad
Unfavorable Publicity
Positive changes in ad
Favorable Publicity
Finally, in order to rule out the alternative explanation that the positive
relationship between advertising and sales might be attributable to firms’ size,
advertising intensity was also examined. Along this line, favorable publicity was
better than unfavorable publicity in generating much higher sales revenues in both
low and high advertising intensity. As shown in Figure 14, however, even though
95
firms spent more on advertising (high advertising intensity), when unfavorable
publicity was dominant, sales revenues were far inferior to those of firms with
low ad intensity and unfavorable publicity. The results imply that when negative
news coverage was dominant, incremental advertising did not have a positive
effect and may even have had a negative effect. This result is worth comparing
with Figure 12A, suggesting that regardless of the type of publicity, incremental
advertising had a positive effect on sales revenues. Figure 14 contains the
interaction effect of advertising intensity and publicity on sales revenues.
Figure 14
Interaction Effect of Advertising Intensity and Publicity on Sales
15000
14500
mm $
14000
13500
13000
12500
12000
11500
Low ad intensity
High ad intensity
Unfavorable Publicity
96
Favorable Publicity
Hypotheses Test
Data Analysis Procedure
The main purpose of this study is to provide a comprehensive analysis
about the relationships between marketing communication and corporate
reputation and between marketing communication and sales revenue, through a
time-series analysis of longitudinal data of a 21-year period. The comprehensive
analysis is addressed by selecting a significant subset of predictor variables. In
order to select a subset of predictor variables, regression analysis was employed.
When time-series data are used in regression analysis, often the error term
is not independent through time. The errors are serially correlated or
autocorrelated. If the error term is autocorrelated, the efficiency of ordinary leastsquares (OLS) parameter estimates is adversely affected, and standard error
estimates are biased. Therefore, it is not desirable to use ordinary regression
analysis for time-series data since the assumptions on which the classical linear
regression model is based will usually be violated.
Violation of the independent errors assumption has three important
consequences for ordinary regression. First, statistical tests of the significance of
the parameters and the confidence limits for the predicted values are not correct.
Second, the estimates of the regression coefficients are not as efficient as they
97
would be if the autocorrelation were taken into account. Third, since the ordinary
regression residuals are not independent, they contain information that can be
used to improve the prediction of future values (Ostrom, 1990).
The SAS AUTOREG procedure solves this problem by augmenting the
regression model with an autoregressive model for the random error, thereby
accounting for the autocorrelation of the errors. The AUTOREG procedure is a
generalized least-squares regression approach that uses estimates of
autocorrelation in a model’s residuals in estimating structural parameters and
significant levels.
That is, the AUTOREG adjusts for autocorrelation in the annual data of
this study. This adjustment produces better estimates of regression parameters.
The AUTOREG assumes that the error term is autoregressive with a given ρ for
the estimation of the parameters. The parameter estimates are similar to least
squares estimates but the standard errors may be different, affecting significance.
By simultaneously estimating the regression coefficients B and autoregressive
error model parameters ρ, the AUTOREG procedure corrects the regression
estimates for autocorrelations. The autoregressive error model for the hypothesis
test is:
Yt = B1 + B2 Xt + B3 Xt + ………. Bk Xkt + et
et = ρet–1 + vt
[Equation 9]
98
where Yt = dependent variable ; Xkt = independent variables.
This study used the maximum-likelihood approach in the SAS AUTOREG
procedure (SAS Institute, 1999) to analyze annual data, taking into account any
significant autocorrelation at lags of one and two years.
Data Analysis Approach
A consistent model-building approach was used to decide which variables
were significant in predicting corporate reputation and sales revenue, respectively.
A stepwise regression analysis with backwards elimination of non-significant
predictors was utilized to select a subset of predictor variables. First, for each
company, advertising, publicity, corporate reputation, sales, and other predictor
variables were included in the regression equation. Then, the least significant
predictor variable was dropped and another regression analysis was performed.
The analysis was continued until the final model was found, with all variables
significant at the 5% level of significance (p < .05). Finally, the R squares of
sequential models were compared to ensure that there was not a significant drop
in explained variance.
Specifically, two sets of regression analyses were performed: (1) a
regression model for the marketing communication-corporate reputation
99
relationship and (2) a regression model for the marketing communication-sales
revenue relationship. The first regression was run to examine the relationship
between marketing communications (advertising and publicity) and corporate
reputation. For each company, advertising, publicity, dividend yield,
diversification, market-to-book ratio (M/B ratio), profitability, and firm size were
regressed on corporate reputation as the dependent variable. Then, the least
significant variable was dropped (p < .05) and another regression analysis was
performed. This procedure continued until all independent variables were
significant in the regression model. Finally, the R squares of the sequential
models were compared to see if there was a significant drop in explained variance.
The regression model used to examine the relationship between
advertising, publicity, and corporate reputation is as follows:
CRit = α + B1 ADit-1 + B2 PBit + B3 DYt + B4 MBit + B5 DVit-1 + B6 PFit-1 +
[Equation 10]
B7 FSit + eit
where
CRit = corporate reputation of firm i in year t ;
ADit-1 = advertising expenditures of firm i in year t-1;
PBit = publicity of firm i in year t;
100
DYit = dividend yield of firm i in year t;
MBit = market-to-book ratio of firm i in year t;
DVit-1 = diversification of firm i in year t-1;
PFit-1 = profit of firm i in year t-1;
FSit = firm size of firm i in year t; and
et = ρet–1 + vit (|ρ| < 1, et is the error term, and vt is a random variable with
a zero mean, constant variance, and zero correlation with
the other errors).
As noted previously in the methodology section, this study considered the
impact of the firm’s advertising, profitability, and diversification in Period t-1 on
corporate reputation in Period t, in accordance with the time lags suggested by
previous reputation studies (Fombrun and Shanley, 1990; McGuire, Sundgren,
and Schneeweis, 1988). Also, these lagged measures of profitability and
diversification on corporate reputation preclude a potential reverse-causality
explanation of the effects. It indicates that prior financial performance is a
variable influencing reputation rather than the reverse.
Second, the same regression analysis was utilized to examine the
relationship between marketing communications (advertising and publicity) and
sales revenue. To explore this relationship, new relevant factors – corporate
101
reputation, research and development (R&D) expenditures, and focus of the firm were included in the regression model. Firm size was also controlled for this
model. That is, advertising, publicity, and other predictor variables were used in
the regression equation with corporate sales revenue as the dependent variable.
Again, the least significant predictor was dropped and another regression analysis
was performed. This analysis continued until a final model was found with all
variables significant (p < .05). Also, the R squares of sequential models were
compared to confirm that there was no significant drop in explained variance.
In order to examine the relationship between marketing communications
and sales revenues, the following model is used.
SRit = α + B1 ADit-1 + B2 PBit + B3 CRit-1 + B4 RDit-1 + B5 FFit + B6 FSit +
[Equation 11]
eit
where
SRit = sales revenues of firm i in year t ;
ADit-1 = advertising expenditures of firm i in year t-1;
PBit = publicity of firm i in year t;
CRit-1 = corporate reputation of firm I in year t-1;
RDit-1 = R&D expenditures of firm i in year t-1;
102
FFit = focus of the firm of firm i in year t;
FSit = firm size of firm i in year t; and
et = ρet–1 + vit (|ρ| < 1, et is the error term, and vt is a random variable with
a zero mean, constant variance, and zero correlation with
the other errors).
Just as in the first regression model, this study considered the impact of
the firm’s advertising, corporate reputation, and R&D in Period t-1 on sales
revenue in Period t to consider carryover effects and rule out the explanation of a
potential reverse causality.
Data Analysis Results
Prior to hypotheses testing, this study explored visual representations of
the marketing communication variables, corporate reputation, and sales
relationships for each company: advertising – publicity – corporate reputation
relationship and advertising – publicity – sales relationship. Detailed information
of visual representations is presented in Appendix B.
103
Also, data transformations were taken for achieving normality and
linearity of data (e.g., logarithm transformation, square root transformation).
Details on data transformations for each variable are listed in Appendix C.
Testing for Autocorrelations
Due to the autocorrelative nature of time-series data, a Durbin-Watson test
(H0: there is no positive or negative autocorrelation.) was performed to test for the
presence of autocorrelations in the data. Table 3 shows the results of the DurbinWatson test for each company. In most cases, test results of Durbin-Watson test
were highly significant with p < .05 for the null hypothesis of no autocorrelation.
This suggests that the general regression model would not be appropriate for the
testing of these data and autocorrelation correction is needed.
Testing for Heteroscedasticity
Another important assumption of the ordinary regression model is
homoscedasticity, which means the errors have the same variance throughout the
sample. If the error variance is not consistent, the data are said to show
heteroscedasticity. Since ordinary least-square (OLS) regression assumes
constant error variance, heteroscedasticity causes the OLS estimates to be
inefficient. Also, heteroscedasticity can make the OLS forecast error variance
104
inaccurate since the predicted forecast variance is based on the average variance
instead of the variability at the end of the series. Thus, models that take into
account the changing variance can make more efficient use of the data.
Heteroscedasticity was evaluated by examining OLS residuals using the
AUTOREG. The statistics shown by AUTOREG indicated that heteroscedasticity
was not a problem here.
Table 3
Durbin-Watson Test for Autocorrelations
Dependent Variable =
Corporate Reputation
Company
Durbin-Watson
American standard
Apple Computer
AT&T
Coca Cola
Delta Air Lines
Fortune Brands
Gillette
Johnson & Johnson
Kimberly Clark
Pfizer
PPG Industries
Proctor & Gamble
Sara Lee
Stanley Works
Texas Instruments
United State Tobacco
VF Corp.
Vulcan Materials
1.3378*
1.3859*
2.6504
2.8825
1.7425*
2.0850*
1.3334*
0.9892*
1.2156*
1.7377*
1.8510*
1.8001*
1.8727*
1.4335*
2.8531
1.4899*
2.1599
1.4899*
105
Dependent Variable =
Sales Revenues
American standard
Apple Computer
AT&T
Coca Cola
Delta Air Lines
Fortune Brands
Gillette
Johnson & Johnson
Kimberly Clark
Pfizer
PPG Industries
Proctor & Gamble
Sara Lee
Stanley Works
Texas Instruments
United State Tobacco
VF Corp.
Vulcan Materials
1.8393*
0.7386*
1.1894*
0.6007*
1.5661*
1.5211*
1.8345*
2.0806
1.4905*
1.8820*
2.1260
1.8006*
0.6560*
1.6992*
2.2353
0.6564*
1.1930*
1.8966
* Significant at p < .05
Advertising, Publicity, and Corporate Reputation
For corporate reputation, the full regression models of each company with
all the variables are presented in Table 4. Table 5 contains the final corporate
reputation models for each company. Since this study focuses on the final model
in which the non-significant variables were dropped, the full models with all
predictors are not discussed. The interpretation was made for the final model.
Also, since the intercept parameters have no substantial relevance to
understanding the relationship between market communications and corporate
reputation, they are not discussed.
106
Advertising expenditures showed a significant relationship with corporate
reputation for 12 out of 18 companies and publicity exhibited a significant
association with corporate reputation for 9 out of 18 companies. Both advertising
and publicity simultaneously had a significant relationship to corporate reputation
in 5 companies. In 2 companies, none of the predictors had a significant
relationship to corporate reputation. With respect to the other variables, dividend
policy, diversification, market-to-book ratio, profitability, and firm size, also had
statistically significant relationships with corporate reputation for certain
companies.
The individual final models for each firm indicated that in seven models,
the predictors explained over 90% of the variance in corporate reputation, and
over 80% in four companies. In five companies, the total variance in corporate
reputation explained by predictors was less than 80% (American Standard,74%;
Delta Airlines, 74%; Johnson and Johnson, 66%; Proctor & Gamble, 69%; and
United States Tobacco, 53%).
Specific results of each relationship are as follows:
Advertising-Reputation Relationship
Five companies (Apple Computer, Fortune Brands, Proctor & Gamble,
Sara Lee, and Texas Instruments) showed a positive relationship between
107
advertising expenditures and corporate reputation. Advertising expenditures were
negatively related to corporate reputation in seven companies (AT&T, Coca Cola,
Delta Air Lines, Gillette, Kimberly & Clark, Pfizer, and VF Corp.).
Publicity-Reputation Relationship
In six companies (American Standard, Kimberly Clark, Pfizer, Texas
Instruments, United States Tobacco, and VF Corp.), publicity was positively
associated with corporate reputation. Publicity for Gillette, Johnson & Johnson,
and Stanley Works exhibited a negative relationship to corporate reputation.
Advertising-Publicity-Corporate Reputation Relationship
In Gillette, Kimberly Clark, Pfizer, Texas Instruments, and VF Corp., both
advertising expenditures and publicity simultaneously showed significant
relationships to corporate reputation. However, the direction of the relationship
varied from company to company. Both advertising expenditures and publicity for
Gillette were negatively related to corporate reputation. In Texas Instruments, in
contrast, both advertising expenditures and publicity were positively associated
with corporate reputation. In Kimberly Clark, Pfizer, and VF Corp., advertising
expenditures exhibited a negative relationship, whereas publicity exhibited a
positive relationship to corporate reputation.
108
Other Variables
Other factors, such as dividend policy, market-to-book ratio,
diversification, profit, and firm size, were significantly related to corporate
reputation but the direction of the relationship varied. For example, a firm’s
current dividend yield to its investors had a significant relationship to assessments
of corporate reputation. The current dividend yield showed a positive relationship
with corporate reputation for Delta Air Lines, Fortune Brands, and Kimberly
Clark. Dividend yield was negative for AT&T, Proctor & Gamble, Pfizer, Sara
Lee, Texas Instruments, and VF Corp, suggesting that low dividend yields induce
high assessments of corporate reputation.
A firm’s current market value also affected assessments of a firm’s
reputation. Market-to-book ratio exhibited a significant relationship to corporate
reputation in 12 companies. For Apple Computer, AT&T, Coca Cola, Delta Air
Lines, Gillette, and Kimberly Clark, the current market-to-book ratio was a
positive predictor. However, it was negatively associated for Proctor & Gamble,
Sara Lee, Stanley Works, Texas Instruments, and VF Corp.
With respect to diversification, as discussed previously in the
methodology section, firms with low diversification tended to be more focused
and firms with high diversification were involved in a broad range of business.
109
Diversification is a measure of business relatedness, suggesting that firms with
high scores on the index are more likely to encompass less related business under
their corporate umbrellas than firms with low scores on the index. In this study, as
expected, diversification (business relatedness) was negatively related to
corporate reputation for five companies (Apple Computer, Fortune Brands,
Kimberly Clark, and VF Corp), and it was a positive predictor for only one
company (American Standard).
The previous year’s profit also presented a significant relationship to
assessment of corporate reputation. For Apple Computer, Coca Cola, and Johnson
& Johnson, profitability exhibited a positive relationship with corporate reputation,
and the relationships were negative in Kimberly Clark, Sara Lee, Stanley Works,
and United States Tobacco.
In American Standard, AT&T, Delta Air Lines, Pfizer, Stanley Works,
and Texas Instruments, firm size had a positive association in predicting corporate
reputation, and it was negative in Apple Computer, Fortune Brands, Johnson &
Johnson, Proctor Gamble, Sara Lee, and VF Corp.
110
Table 4
Full Corporate Reputation Models
Corporate Reputation
Independent Variable
B
American Standard
Intercept
Advertising
Publicity
Dividend Policy
Market-to-Book Ratio
Diversification
Profit
Firm Size
Apple Computer
Intercept
Advertising
Publicity
Dividend Policy
Market-to-Book Ratio
Diversification
Profit
Firm Size
AT&T
Intercept
Advertising
Publicity
Dividend Policy
Market-to-Book Ratio
Diversification
Profit
Firm Size
Coca Cola
Intercept
Advertising
Publicity
Dividend Policy
Market-to-Book Ratio
Diversification
Profit
Firm Size
t
p
3.1129
-0.004331
0.4550
0.0297
0.000969
1.8576
-1.3662
0.0277
4.65
-0.66
3.81
0.63
0.33
3.06
-1.71
2.72
0.0007
0.5209
0.0029
0.5398
0.7508
0.0108
0.1153
0.0029
6.3879
0.004145
0.2534
-0.2621
0.0895
-2.0257
3.0160
-0.1569
4.99
3.42
0.53
-1.64
1.72
-2.81
6.36
-3.03
0.0005
0.0065
0.6073
0.1329
0.1170
0.0186
<.0001
0.0126
5.0237
-0.000867
0.4192
-0.3664
0.3251
-0.0629
0.9789
0.008826
3.21
-4.51
0.63
-2.80
3.45
-0.13
1.60
8.58
0.0094
0.0011
0.5449
0.0189
0.0062
0.8981
0.1398
<.0001
8.0230
-0.001297
-0.3567
0.003334
0.0640
-0.0859
5.2038
0.0182
5.66
-2.44
-0.61
0.02
2.33
-0.06
2.86
1.64
0.0001
0.0330
0.5567
0.9844
0.0402
0.9561
0.0154
0.1296
111
Total R2
DFE
0.7769
11
0.9616
10
0.9409
10
0.9228
11
Delta Air
Intercept
Advertising
Publicity
Dividend Policy
Market-to-Book Ratio
Diversification
Profit
Firm Size
Fortune Brands
Intercept
Advertising
Publicity
Dividend Policy
Market-to-Book Ratio
Diversification
Profit
Firm Size
Gillette
Intercept
Advertising
Publicity
Dividend Policy
Market-to-Book Ratio
Diversification
Profit
Firm Size
Johnson & Johnson
Intercept
Advertising
Publicity
Dividend Policy
Market-to-Book Ratio
Diversification
Profit
Firm Size
Kimberly Clark
Intercept
Advertising
Publicity
Dividend Policy
Market-to-Book Ratio
Diversification
Profit
Firm Size
3.3061
-0.005722
0.2114
0.8282
0.4148
0
-0.6501
0.0306
1.45
-1.82
0.24
8.23
4.41
-1.07
2.62
0.1739
0.0938
0.8178
<.0001
0.0008
0.3072
0.0222
13.2058
0.002027
0.3609
0.1789
-0.3247
-8.3119
3.2541
-0.0403
7.70
2.21
1.57
1.58
-1.52
-4.88
2.55
-8.72
<.0001
0.0514
0.1467
0.1458
0.1603
0.0006
0.0287
<.0001
6.7828
-0.000787
-0.2451
0.0513
0.004996
1.5559
0.3435
0.0167
3.46
-1.92
-1.80
0.33
1.96
0.62
0.54
0.68
0.0061
0.0833
0.1027
0.7486
0.0780
0.5505
0.5980
0.5141
10.5493
0.0000742
-0.5037
0.8117
0.2402
-4.2645
4.8151
-0.0251
1.23
0.12
-2.05
1.41
1.41
-0.39
2.35
0.12
0.2432
0.9039
0.0647
0.1851
0.1861
0.7058
0.0384
0.4104
7.8071
-0.000764
0.1886
0.1051
0.1910
-2.9134
2.8617
-0.006960
9.48
-0.85
1.65
1.14
7.88
-5.15
-4.05
-0.80
<.0001
0.4188
0.1383
0.2855
<.0001
0.0009
0.0037
0.4472
112
0.7571
12
0.8884
10
0.9195
10
0.7138
11
0.9874
8
Pfizer
Intercept
Advertising
Publicity
Dividend Policy
Market-to-Book Ratio
Diversification
Profit
Firm Size
PPG Industries
Intercept
Advertising
Publicity
Dividend Policy
Market-to-Book Ratio
Diversification
Profit
Firm Size
Proctor & Gamble
Intercept
Advertising
Publicity
Dividend Policy
Market-to-Book Ratio
Diversification
Profit
Firm Size
Sara Lee
Intercept
Advertising
Publicity
Dividend Policy
Market-to-Book Ratio
Diversification
Profit
Firm Size
7.8071
-0.000764
0.1886
0.1051
0.1910
-2.9134
-2.8617
-0.0006960
9.48
-0.85
1.65
1.14
7.88
-5.15
-4.05
-0.80
<.0001
0.4188
0.1383
0.2855
<.0001
0.0009
0.0037
0.4472
9.1951
-0.001503
-.0.0358
-0.1176
-0.2036
3.0051
-1.1268
-0.0943
1.50
-0.18
-0.31
-0.30
-0.86
0.68
-0.85
-1.22
-0.1763
0.8658
0.7681
0.7717
0.4253
0.5183
0.4241
0.2610
13.2843
0.000266
-0.1071
-0.6182
-0.0352
-1.4914
-1.0379
-0.0305
7.31
5.19
-0.50
-4.15
-1.03
-1.30
-0.99
-3.50
<.0001
0.0003
0.6290
0.0016
0.3272
0.2206
0.3455
0.0050
9.4553
0.000868
0.1015
-0.3763
-0.1045
0.2435
-0.9737
-0.0190
10.26
5.19
0.82
-2.66
-7.34
0.39
-2.69
-6.96
<.0001
0.0003
0.4299
0.0221
<.0001
0.7074
0.0211
0.0003
113
0.9874
8
0.5260
7
0.7291
11
0.9582
11
Stanley Works
Intercept
Advertising
Publicity
Dividend Policy
Market-to-Book Ratio
Diversification
Profit
Firm Size
Texas Instrument
Intercept
Advertising
Publicity
Dividend Policy
Market-to-Book Ratio
Diversification
Profit
Firm Size
United States Tobacco
Intercept
Advertising
Publicity
Dividend Policy
Market-to-Book Ratio
Diversification
Profit
Firm Size
VF Corp.
Intercept
Advertising
Publicity
Dividend Policy
Market-to-Book Ratio
Diversification
Profit
Firm Size
Vulcan Materials
Intercept
Advertising
Publicity
Dividend Policy
Market-to-Book Ratio
Diversification
Profit
Firm Size
8.7267
-0.0112
-0.6237
-0.6988
-1.0712
-1.4022
-9.9415
0.3124
2.42
-0.42
-2.82
-1.44
-5.20
-0.85
-3.14
2.67
0.0339
0.6817
0.0166
0.1787
0.0003
0.4138
0.0094
0.0220
6.0567
0.003765
0.5950
-3.1914
-0.2126
0.4619
0.6162
0.0526
2.53
2.05
1.05
-1.60
-1.44
0.40
-0.54
0.97
0.0644
0.1099
0.3545
0.1839
0.2229
0.7086
0.6171
0.3861
8.5148
0.0434
-0.0527
-0.3554
-0.8308
-0.3458
5.4635
0.0635
1.38
0.09
-0.28
-0.44
-1.12
-0.09
1.69
-0.24
0.2035
0.9295
0.7901
0.6745
0.2946
0.9294
0.1303
0.8141
11.5012
-0.002222
0.2877
-0.7269
-0.6905
-0.6273
0.9083
-0.0236
13.79
-3.70
1.39
-7.22
-4.81
-5.40
0.91
-4.64
<.0001
0.0035
0.1923
<.0001
0.0005
0.0002
0.3847
0.0035
8.5148
0.0434
-0.0527
-0.3554
-0.8308
-0.3458
5.4635
0.0434
1.38
0.09
-0.28
-0.44
-1.12
-0.09
1.69
0.24
0.2035
0.9295
0.7901
0.6745
0.2946
0.9294
0.1303
0.8141
114
0.8978
11
0.9980
4
0.6753
8
0.8784
11
0.6753
8
Table 5
Final Corporate Reputation Models
Corporate Reputation
Independent Variable
B
American Standards
Intercept
Publicity
Diversification
Profit
Firm Size
Apple Computer
Intercept
Advertising
Market-to-Book Ratio
Diversification
Profit
Firm Size
AT&T
Intercept
Advertising
Dividend Policy
Market-to-Book Ratio
Firm Size
Coca Cola
Intercept
Advertising
Market-to-Book Ratio
Profit
Delta Air
Intercept
Advertising
Dividend Policy
Market-to-Book Ratio
Firm Size
Fortune Brands
Intercept
Advertising
Dividend Policy
Diversification
Firm Size
t
p
2.8298
0.3934
2.3427
-1.7490
0.0224
5.62
5.52
5.11
-3.65
3.85
<.0001
<.0001
0.0002
0.0026
0.0018
6.9322
0.005531
0.1287
-2.0789
3.2216
-0.2014
12.37
6.95
2.49
-5.10
9.94
-4.92
<.0001
<.0001
0.0286
0.0003
<.0001
0.0004
5.5795
-0.000796
-0.3618
0.3618
0.009407
19.20
-6.71
-4.69
7.83
13.42
<.0001
<.0001
0.0004
<.0001
<.0001
7.6139
-0.000905
0.0629
4.0019
45.63
-9.86
6.29
5.26
<.0001
<.0001
<.0001
<.0001
3.6379
-0.004902
0.8439
0.3984
0.0301
6.37
-2.84
8.90
6.53
2.84
<.0001
0.0117
<.0001
<.0001
0.0131
13.4856
0.003025
0.2675
-9.5828
-0.0366
13.31
4.12
2.72
-6.14
-7.06
<.0001
0.0012
0.0176
<.0001
<.0001
115
Total R2
DFE
0.7382
14
0.9514
12
0.9293
13
0.9013
15
0.7381
14
0.8031
13
Gillette
Intercept
Advertising
Publicity
Market-to-Book Ratio
Johnson & Johnson
Intercept
Publicity
Profit
Firm Size
Kimberly Clark
Intercept
Advertising
Publicity
Dividend Policy
Market-to-Book Ratio
Diversification
Profit
Pfizer
Intercept
Advertising
Publicity
Dividend Policy
Firm Size
PPG Industries
None
Proctor & Gamble
Intercept
Advertising
Dividend Policy
Market-to-Book Ratio
Firm Size
Sara Lee
Intercept
Advertising
Dividend Policy
Market-to-Book Ratio
Profit
Firm Size
Stanley Works
Intercept
Publicity
Market-to-Book Ratio
Profit
Firm Size
8.2698
-0.000535
-0.2067
0.005158
20.51
-3.16
-1.85
2.25
<.0001
0.0070
0.0482
0.0409
9.7159
-0.4984
3.7377
-0.0148
11.48
-2.25
2.78
-2.25
<.0001
0.0397
0.0141
0.0491
7.1242
-0.001524
0.2438
0.1783
0.2097
-2.5317
-3.2697
19.08
-3.19
2.70
2.67
9.39
-5.08
-5.23
<.0001
0.0110
0.0243
0.0257
<.0001
0.0007
0.0005
6.2269
-0.000801
0.8482
-0.6209
0.0257
8.79
-4.46
3.11
-8.48
3.56
<.0001
0.0006
0.0083
<.0001
0.0035
11.2025
0.000237
-0.5029
-0.0728
-0.0228
14.68
5.17
-4.54
-3.45
-3.59
<.0001
0.0001
0.0005
0.0039
0.0030
10.0646
0.000810
-0.4535
-0.1075
-0.9390
-0.0183
31.11
5.86
-4.53
-9.34
-2.76
-7.45
<.0001
<.0001
0.0006
<.0001
0.0161
<.0001
5.2458
-0.5701
-0.8384
-10.9056
0.2833
4.49
-3.05
-10.23
-4.16
-3.05
0.0005
0.0086
<.0001
0.0010
<.0001
0.9118
14
0.6610
15
0.9864
9
0.8548
13
0.6908
14
0.9554
13
0.8775
116
14
Texas Instrument
Intercept
Advertising
Publicity
Dividend Policy
Market-to-Book Ratio
Firm Size
United States Tobacco
Intercept
Publicity
Profit
VF Corp.
Intercept
Advertising
Publicity
Dividend Policy
Market-to-Book Ratio
Diversification
Firm Size
Vulcan Materials
None
7.0838
0.002558
0.3533
-2.3448
-0.1481
0.0299
65.59
5.86
11.30
-15.41
-9.71
6.82
<.0001
0.0001
<.0001
<.0001
<.0001
0.0005
4.9211
0.8909
-1.0798
9.11
3.52
-1.75
<.0001
0.0028
0.0496
11.3546
-0.002158
0.4540
-0.7334
-0.6954
-0.6931
-0.0258
14.25
-3.83
2.97
-7.88
-5.17
-8.04
-6.22
<.0001
0.0024
0.0118
<.0001
0.0002
<.0001
<.0001
0.9975
6
0.5333
16
0.8722
12
Advertising, Publicity, and Sales Revenue
For sales revenue, the full models with all variables are presented in Table
6 and the final sales revenue models for each company are shown in Table 7.
Advertising expenditures were significantly associated with sales revenue for 14
out of 18 companies and publicity exhibited a significant relationship with sales
revenue for five out of 18 companies. Both advertising and publicity had a
significant relationship with sales revenue for four companies. In contrast to the
marketing communication and corporate reputation relationship, there was no
117
company for which none of the predictors had a significant relationship with sales
revenue. Just as in the models examining the relationships with corporate
reputation, control variables, such as reputation, R&D, focus of the firm, and firm
size, showed significant relevance to sales revenue.
As shown in Table 7, the individual final models indicated that the
predictors explained over 90% of the variance in sales revenue in all but one
model (Delta, 85%). The following are specific results of each relationship in the
final sales model.
Advertising-Sales Relationship
In contrast to corporate reputation, the relationships between predictors
and sales revenue were straightforward. Among 15 companies in which
advertising expenditures had a significant relationship with sales revenues –
American Standard, AT&T, Coca Cola, Fortune Brands, Gillette, Johnson &
Johnson, Kimberly Clark, Pfizer, PPG Industries, Proctor & Gamble, Sara Lee,
Stanley Works, Texas Instruments, United States Tobacco, and VF Corp. – all but
two companies (PPG Industries and Stanley Works) exhibited a significant
positive relationship between advertising expenditures and sales revenues. PPG
Industries and Stanley Works presented a negative association with sales revenue.
118
Publicity-Sales Relationship
Publicity had a negative relationship with sales revenue for Apple
Computer and Coca Cola. Publicity for Johnson & Johnson, Texas Instruments,
and United States Tobacco showed a positive relationship to sales revenue.
Advertising-Publicity-Sales Relationship
In addition, in these three companies – Johnson & Johnson, Texas
Instruments, and United States Tobacco – advertising expenditures, as well as
publicity, exhibited a significant relationship to sales revenues, and the
relationships were also all positive. Both advertising and publicity for Coca Cola
presented a significant association with sales revenue but their directions were the
opposite: positive advertising effect and negative publicity effect on sales revenue.
Other Variables
The relationship between marketing communications and sales revenue
might be attributed to other factors besides advertising and publicity. For this
reason, other factors such as corporate reputation, focus of the firm, R&D, and
firm size, were included in marketing communication-sales models to explain the
variance in sales revenue.
119
Corporate reputation presented a significant association with sales revenue
in eight companies – Coca Cola, Delta Air Lines, Gillette, Pfizer, PPG Industries,
Proctor & Gamble, Stanley Works, and Vulcan Materials. The direction of the
relationship varied. Coca Cola, Proctor & Gamble, and Vulcan Materials
exhibited a positive relationship, but in the other five companies, reputation had a
negative relationship with sales revenue. Unlike prior studies that demonstrated
the positive effect of corporate reputation on market performance, a positive
relationship was found only in a small number of companies.
Focus of the firm exhibited a significant relationship in seven companies –
American Standard, AT&T, Gillette, Johnson & Johnson, Kimberly Clark, Texas
Instruments, and VF Corp. – and the relationship was positive in all but two
companies (Gillette and Texas Instruments). A positive relationship indicated that
firms with higher focus (or firms with low diversification) exhibited much higher
sales revenues.
R&D was also significant for predicting sales in eleven companies American Standard, AT&T, Fortune Brands, Gillette, Johnson & Johnson, Pfizer,
PPG Industries, Proctor & Gamble, Stanley Works, Texas Instruments, and
Vulcan Materials. Only one company – Fortune Brands – presented a negative
relationship between R&D and sales revenue. The relationship was positive in the
120
rest of them, suggesting that the prior year’s higher R&D expenditures generate
higher sales revenues.
Firm size revealed a significant relationship with sales in nine companies
– Apple Company, AT&T, Coca Cola, Delta Air Lines, Gillette, Kimberly Clark,
PPG Industries, Stanley Works, and VF Corp. The relationship was all positive in
all but one company, PPG Industries.
Table 6
Full Sales Revenue Models
Sales
Independent Variable
B
American Standards
Intercept
Advertising
Publicity
Reputation
Focus of the firm
R&D
Firm Size
Apple Computer
Intercept
Advertising
Publicity
Reputation
Focus of the firm
R&D
Firm Size
t
p
-1315
57.8220
608.8053
-383.6027
1470
23.4174
-1020
-0.18
4.47
1.74
-0.68
3.09
1.44
-0.48
0.8601
0.0008
0.1071
0.5092
0.0093
0.6384
0.1759
-6864
2.3248
-2890
436.0784
-0.5764
7015
-1.07
0.65
-1.72
0.63
3.26
-0.30
0.3049
0.5254
0.1110
0.5417
0.0068
0.7660
121
Total R2
DFE
0.9679
12
0.8945
12
AT&T
Intercept
Advertising
Publicity
Reputation
Focus of the firm
R&D
Firm Size
Coca Cola
Intercept
Advertising
Publicity
Reputation
Focus of the firm
R&D
Firm Size
Delta Air
Intercept
Advertising
Publicity
Reputation
Focus of the firm
R&D
Firm Size
Fortune Brands
Intercept
Advertising
Publicity
Reputation
Focus of the firm
R&D
Firm Size
Gillette
Intercept
Advertising
Publicity
Reputation
Focus of the firm
R&D
Firm Size
-16153
8.7535
-1419
-1088
4018
5.2540
9649
-0.75
6.74
-0.23
-0.82
5.71
2.92
3.55
0.4671
<.0001
0.8239
0.4274
0.0001
0.0139
0.0046
-18247
9.7310
-2136
2200
-284.8108
2333
-3.57
9.37
-1.58
6.11
-0.65
2.03
0.0034
<.0001
0.1373
<.0001
0.5292
0.0636
-14512
12.0333
832.3389
376.7340
5189
-1.16
1.17
0.83
1.00
1.81
0.2653
0.2634
0.4178
0.3362
0.0911
-200.2646
14.8689
-216.9776
366.7182
87.2298
-40.2867
-195.6717
-0.07
8.91
-0.87
1.66
1.46
-2.59
-0.31
0.9686
<.0001
0.4012
0.1258
0.1718
0.0252
0.7590
-4090
2.5920
2.0379
-1174
-2370
7451
34.6467
-1.39
3.21
0.01
-3.67
-3.04
6.61
3.12
0.1920
0.0083
0.9942
0.0037
0.0112
<.0001
0.0098
122
0.9631
11
0.9721
15
0.9308
14
0.9304
11
0.9944
11
Johnson & Johnson
Intercept
Advertising
Publicity
Reputation
Focus of the firm
R&D
Firm Size
Kimberly Clark
Intercept
Advertising
Publicity
Reputation
Focus of the firm
R&D
Firm Size
Pfizer
Intercept
Advertising
Publicity
Reputation
Focus of the firm
R&D
Firm Size
PPG Industries
Intercept
Advertising
Publicity
Reputation
Focus of the firm
R&D
Firm Size
Proctor & Gamble
Intercept
Advertising
Publicity
Reputation
Focus of the firm
R&D
Firm Size
-13900
6.3398
4529
69.0839
1067
5.3511
762.7509
-0.99
11.93
6.61
0.14
1.37
21.47
0.21
0.3401
<.0001
<.0001
0.8922
0.1960
<.0001
0.8409
-25542
24.8488
-139.7005
2668
109.1321
23.9562
1343
-6.02
4.24
-0.76
5.42
0.93
2.71
1.06
0.0002
0.0022
0.4648
0.0004
0.3765
0.0239
0.3185
-10734
2.8617
-352.4315
-7923.4018
-253.2811
2.9455
58583
-0.49
1.18
-0.18
-0.58
-0.21
7.81
0.68
0.6317
0.2627
0.8621
0.5732
0.8342
<.0001
0.5120
68845
-35.1401
-255.1713
-1247
565.5398
38.6610
-17681
5.19
-2.87
-1.61
-2.70
2.14
9.47
-5.36
0.0000
0.0207
0.1450
0.0270
0.0651
<.0001
0.0007
-21917
6.2051
-651.3360
2328
-1078
7.6303
3220
-1.75
12.61
-0.53
2.36
-1.86
6.79
1.57
0.1060
<.0001
0.6069
0.0358
0.0874
<.0001
0.1430
123
0.9987
12
0.9976
9
0.9895
11
0.9484
8
0.9953
12
Sara Lee
Intercept
Advertising
Publicity
Reputation
Focus of the firm
R&D
Firm Size
Stanley Works
Intercept
Advertising
Publicity
Reputation
Focus of the firm
R&D
Firm Size
Texas Instrument
Intercept
Advertising
Publicity
Reputation
Focus of the firm
R&D
Firm Size
United States Tobacco
Intercept
Advertising
Publicity
Reputation
Focus of the firm
R&D
Firm Size
VF Corp.
Intercept
Advertising
Publicity
Reputation
Focus of the firm
R&D
Firm Size
6883
2.7942
273.7828
209.4536
-1477
2385
0.48
3.46
1.23
0.33
-3.30
1.02
0.6364
0.0042
0.2422
0.7490
0.0057
0.3256
1492
3.0959
98.7915
-594.1307
-111.0501
64.8727
1246
0.71
0.32
0.86
-5.32
-1.87
1.50
1.24
0.5078
0.7650
0.4308
0.0031
0.1200
0.1941
0.2705
-10886
16.7522
2291
1047
-1672
2.2244
2848
-0.43
1.43
2.38
0.80
-2.92
0.92
0.61
0.6846
0.2113
0.0629
0.4615
0.0329
0.4018
0.56860
1462
2.0515
31.3927
1.8246
13.7677
-310.0418
2.41
2.09
1.86
0.15
1.04
-1.20
0.0328
0.0587
0.0869
0.8869
0.3174
0.2522
-1631
14.1592
-11.2383
-113.5343
50.4862
926.8672
-1.17
13.66
-0.19
-1.48
2.51
2.65
0.2621
<.0001
0.8490
0.1625
0.0259
0.0199
124
0.9759
13
0.9826
5
0.9326
5
0.9948
12
0.9927
13
Vulcan Materials
Intercept
Advertising
Publicity
Reputation
Focus of the firm
R&D
Firm Size
0.9842
-7693
106.0030
29.9206
148.9164
9.4970
17.3429
4109
-10.82
0.70
0.42
3.28
0.10
1.85
10.85
9
<.0001
0.5011
0.6848
0.0096
0.9224
0.0971
<.0001
Table 7
Final Sales Revenue Models
Sales Revenue
Independent Variable
B
American Standards
Intercept
Advertising
Focus of the firm
R&D
Apple Computer
Intercept
Publicity
Firm Size
AT&T
Intercept
Advertising
Focus of the firm
R&D
Firm size
Coca Cola
Intercept
Advertising
Publicity
Reputation
Firm size
Delta Air
Intercept
Reputation
Firm Size
t
p
-5109
63.1090
1212
13.4000
-4.23
6.68
3.75
2.17
0.0007
<.0001
0.0019
0.0468
- 8213
- 1677
7692
-2.04
710.4766
1469
0.0587
0.0313
<.0001
-25185
8.7599
3986
4.2269
9863
-2.62
8.15
6.18
4.10
4.66
0.0212
<.0001
<.0001
0.0012
0.0004
-17830
10.2676
-2568
2243
1971
-3.52
16.19
-2.42
6.57
1.89
0.0034
<.0001
0.0298
<.0001
0.0498
-21320
-1648
10313
-2.22
-3.83
4.79
125
0.0409
0.0015
0.0002
Total R2
DFE
0.9647
15
0.8955
16
0.9608
13
0.9713
14
0.8478
16
Fortune Brands
Intercept
Advertising
R&D
Gillette
Intercept
Advertising
Reputation
Focus of the firm
R&D
Firm size
Johnson & Johnson
Intercept
Advertising
Publicity
Focus of the firm
R&D
Kimberly Clark
Intercept
Advertising
Firm Size
Pfizer
Intercept
Advertising
Reputation
R&D
PPG Industries
Intercept
Advertising
Reputation
Focus of the firm
R&D
Firm size
Proctor & Gamble
Intercept
Advertising
Reputation
R&D
Sara Lee
Intercept
Advertising
Firm size
987.7746
15.7598
-32.2328
1.59
11.04
-4.91
0.0316
<.0001
0.0002
-4079
2.5899
-1172
-2370
34.6684
7446
-1.74
3.38
-4.11
-3.18
7.41
3.33
0.1075
0.0054
0.0014
0.0079
0.0060
<.0001
-9975
6.3420
4530
1042
5.4100
-7.27
13.33
7.55
4.71
38.54
<.0001
<.0001
<.0001
0.0003
<.0001
-15830
12.7817
5090
-2.24
7.14
2.52
0.0434
<.0001
0.0257
8714
4.1880
-808.9682
3.2195
2.80
8.44
-1.92
17.07
0.0141
<.0001
0.0752
<.0001
80299
-44.7174
-1424
811.1557
39.5913
-20874
6.19
-3.56
-2.82
3.39
8.74
-6.80
0.0002
0.0061
0.0202
0.0080
<.0001
<.0001
-7824
6.1519
1649
6.4949
-1.06
12.06
1.76
5.64
0.3075
<.0001
0.0485
<.0001
-50930
2.2784
13109
-3.76
2.16
4.50
0.0017
0.0462
0.0004
126
0.9109
15
0.9944
12
0.9987
14
0.9902
13
0.9880
14
0.9356
9
0.9933
15
0.8987
16
Stanley Works
Intercept
Reputation
R&D
Texas Instrument
Intercept
Advertising
Publicity
Focus of the firm
R&D
United States Tobacco
Intercept
Advertising
Publicity
VF Corp.
Intercept
Advertising
Focus of the firm
Firm size
Vulcan Materials
Intercept
Reputation
R&D
3231
-452.5666
134.6268
16.25
-17.17
10.47
<.0001
<.0001
<.0001
7138
22.9247
2354
-1670
1.9865
2.72
2.85
3.38
-4.09
3.35
0.0298
0.0247
0.0117
0.0046
0.0122
1014
2.8882
25.3971
2.13
3.33
1.87
0.0499
0.0045
0.0807
-2374
14.5289
53.5061
890.4542
-1.94
13.89
2.58
2.63
0.0409
<.0001
0.0211
0.0190
-8268
164.6278
4506
-30.44
5.32
33.22
<.0001
<.0001
<.0001
0.9751
9
0.9223
7
0.9935
15
0.9913
15
0.9654
16
Table 8 summarizes the significant marketing communication variables
and their direction of the relationship in predicting corporate reputation and sales
revenues. Each firm was classified into one of four categories based on its
industry and product type (presented in Table 1): consumer products firms
(selling products to final consumers), industrial products firms (selling
manufactured products to other firms), consumer/industrial products firms (selling
products to both final consumers and other firms), and services firms (service
127
providers). The sample consists of 10 consumer products firms, 4 industrial
products firms, 2 consumer/industrial products firms, and 2 services firms.
128
Table 8
Summary of Findings
DV: Reputation
Companies
DV: Sales
Firm Classification
adv
publicity
adv
+
+
American standard
Consumer/Industrial
Products Firm
Apple Computer
Consumer Products Firm
+
AT&T
Services Firm
−
+
Coca Cola
Consumer Product Firm
−
+
Delta Air Lines
Services Firm
−
Fortune Brands
Industrial Products Firm
+
Gillette
Consumer Products Firm
−
Johnson & Johnson
Consumer Products Firm
Kimberly Clark
Consumer Products Firm
Pfizer
Consumer Products Firm
PPG Industries
Industrial Products Firm
Proctor & Gamble
Consumer Products Firm
+
+
Sara Lee
Consumer Products Firm
+
+
Stanley Works
Consumer/Industrial
Products Firm
Texas Instruments
Industrial Products Firm
United States
Tobacco
Consumer Products Firm
VF Corp.
Consumer Products Firm
Vulcan Materials
Industrial Products Firm
−
−
+
−
+
−
+
−
+
+
−
+
+
+
−
+
−
+ = significant, positive impact; − = significant, negative impact.
129
publicity
−
−
+
+
+
+
+
+
+
+
According to the results of this study, all but four companies (Delta Air
Lines, PPG Industries, Stanley Works, and Vulcan Materials) possessed at least
one marketing communication variable that had a positive effect on corporate
reputation or sales revenue. For these four companies, firms selling products to
mainly industry-related areas, advertising and publicity were not significantly
related to corporate reputation and sales revenue, or they had a negative influence
on reputation and sales.
There is only one company – Texas Instruments – in which all four
hypotheses were supported: positive advertising-reputation relationship, positive
publicity-reputation relationship, positive advertising-sales relationship, and
positive publicity-sales relationship. In United States Tobacco, three positive
relationships of publicity and reputation, advertising and sales revenue, and
publicity and sales revenue were supported, but no significant relationship
between advertising and reputation was found. Figure 15 presents the visual
information on advertising, publicity, corporate reputation and sales revenue of
these two companies. According to this visual information, the two firms’
advertising expenditure and publicity exhibit a relatively consistent flow with
their reputation and sales revenue. Information for other companies appears in
Appendix B.
130
Figure 15
Visual Information of Advertising, Publicity, Reputation, and Sales
A: Visual Information of Advertising, Publicity, and Reputation
Advertising
Publicity
20
05
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
Texas Instruments (1985-2005)
Reputation
Note: in case of publicity, above the line (+) refers to favorable publicity and
below the line (-) refers to unfavorable publicity.
B: Visual Information of Advertising, Publicity, and Sales
Advertising
Publicity
20
05
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
Texas Instruments (1985-2005)
Sales
Note: in case of publicity, above the line (+) refers to favorable publicity and
below the line (-) refers to unfavorable publicity.
131
C: Visual Information of Advertising, Publicity, and Reputation
Advertising
Publicity
20
05
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
United States Tobacco (1985-2005)
Reputation
Note: in case of publicity, above the line (+) refers to favorable publicity and
below the line (-) refers to unfavorable publicity.
D: Visual Information of Advertising, Publicity, and Sales
Advertising
Publicity
20
05
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
United States Tobacco (1985-2005)
Sales
Note: in case of publicity, above the line (+) refers to favorable publicity and
below the line (-) refers to unfavorable publicity.
132
Hypotheses Testing Results
The findings provide some support for Hypothesis 1: advertising has a
positive influence on corporate reputation. As we show in Tables 5 and 8 (final
reputation model and summary table), this hypothesis is supported through five
companies (Apple Computer: t = 6.95, p < .01; Fortune Brands: t = 4.12, p <.01;
Proctor & Gamble: t = 5.17, p < .01; Sara Lee: t = 5.86, p < .01; Texas
Instruments: t = 5.86, p < .01). Contrary to expectation, time-series analysis of 18
companies did not strongly support the hypothesis of this study.
Hypothesis 2 predicts that publicity would have a positive impact on
corporate reputation, suggesting that favorable publicity is related to favorable
judgment of corporate reputation. As seen in Tables 5 and 8, favorable publicity
led to favorable corporate reputation for six companies (American Standard: t =
5.52, p <.01; Kimberly Clark: t = 2.70, p <.01; Pfizer: t = 3.11, p < .01; Texas
Instruments: t = 11.30; p < .01; United States Tobacco: t = 3.52, p < .01; VF
Corp.: t = 2.97, p < .01), thus suggesting a positive impact of publicity on
corporate reputation. However, Hypothesis 2 was also not strongly supported by
the finding of this study. Only one third of the sample companies included in the
study support this hypothesis. This finding is consistent with Fombrun and
Shanley’s study (1990) that failed to find a positive relationship between the
133
volume of nonnegative media coverage and a firm’s reputation. However, they
found an interaction of a firm’s diversification with media exposure. That is, in
their study, the amount of media visibility and the extent of nonnegative coverage
did not influence assessments of corporate reputation, but they had a significant
influence on corporate reputation for diversified firms. Thus, further study that
investigates whether there is any interaction effect of publicity with a firm’s other
characteristics, such as a firm’s financial or strategy variables, is necessary.
As indicated in tables 7 and 8 (final sales model and summary table),
Hypothesis 3 – advertising has a positive impact on sales revenue – is supported
through 13 companies (American Standard: t = 6.68, p < .01; AT&T: t = 8.15, p
< .01; Coca Cola: t = 16.19, p < .01; Fortune Brands: t = 11.04, p < .01; Gillette: t
= 3.38, p < .01; Johnson & Johnson: t = 13.33, p < .01; Kimberly Clark: t = 7.14,
p < .01; Pfizer: t = 8.44, p < .01; Proctor & Gamble: t = 12.06, p < .01; Sara Lee: t
= 2.16, p < .01; Texas Instruments: t = 2.85, p < .01; United States Tobacco: t =
3.33, p < .01; VF Corp.: t = 13.89, p < .01). Of four hypotheses of this study,
Hypothesis 3 is the most well supported by most companies included in the study.
While many prior studies have examined the advertising and sales revenue
relationship in a variety of contexts, no previous research has examined the
relationship between advertising and sales revenue in terms of considering the
publicity effect in a model using a longitudinal data set. Therefore, it is difficult to
134
compare the findings of this study with the results of prior studies. However, this
finding confirms our general intuition about the advertising and sales relationship,
implying a positive relationship.
As shown in Tables 7 and 8, Hypothesis 4, positing a positive impact of
publicity on sales revenue, is supported by only three companies (Johnson &
Johnson: t = 7.55, p < .01; Texas Instruments: t = 3.38, p < .01; United States
Tobacco: t = 1.87, p < .01). Unlike what the present author expected, however,
this hypothesis was supported by the fewest number of companies. Also the
finding of this study is inconsistent with a prior study (Deephouse, 2000) that
found a positive relationship between media favorableness and financial
performance.
The finding from Hypothesis 4 that demonstrated that the positive impact
of publicity on sales revenues was supported by the fewest number of companies
appears to indicate that there might exist a different way to measure the
contributions of public relations to market performance. For example, Fombrun
(1996) asserted that the objectives of strategic public relations and corporate
communication can and should extend beyond achieving immediate financial
targets. Accordingly, many public relations and corporate communications focus
on objectives such as building good community relations and improving the
organization’s reputation. Grunig and Hunt (1984) argued that public relations
135
goals and organizational goals should be differentiated. In general, profitability
and revenue are listed as both the most common and the ultimate goals in an
organization (Campbell, 1977; Seashore and Yuchman, 1967). In other words, the
goal of public relations may not be to contribute to the bottom line, but public
relations can contribute to the bottom line by achieving its goals. Then, it can be
assumed that public relations builds corporate reputations, which in turn
contributes to generate market performance. If so, the strength of the relationship
between publicity and market performance will increase as the corporate
reputation increases. In other words, the contribution of public relations to market
performance may be more accurately assessed by examining the moderating role
of corporate reputation. Thus, further studies that investigate how the corporate
reputation moderates the relationship between public relations and market
performance would be useful to measure the contribution of public relations to
market performance.
With respect to the effect of both advertising and publicity on corporate
reputation, only one company (Texas Instruments) simultaneously supported
Hypotheses 1 and 2, suggesting a positive effect of both advertising and publicity
on corporate reputation. With respect to Hypotheses 3 and 4, a positive
association of advertising and publicity with sales revenue was supported in three
companies (Johnson & Johnson, Texas Instruments, and United States Tobacco).
136
Additional Analysis
Reverse Causality
This study performed additional analyses to examine a few alternative
hypotheses regarding the reverse causality.
The Effect of Corporate Reputation
Hypotheses 1 and 2 examined the effect of advertising and publicity on
corporate reputation. That is, in this study, corporate reputation was a response
variable but it can be a predictor variable. Even though this study considered the
advertising effect in period t-1 on corporate reputation in period t to eliminate
reverse causation, there may still exist an alternative hypothesis that corporate
reputation increases the effect of marketing communication (Yoon, Guffey, and
Kijewski, 1993).
Also, although this study focuses on the influences of financial variables
on corporate reputation, there is a reverse causality concern between financial
performance and reputation measure (McGuire et al., 1990). Thus, an alternative
hypothesis that corporate reputation increases a firm’s performance is worth
investigating.
137
The reverse causality was evaluated using Granger causality Wald tests
(Granger, 1969), which examine whether a dependent variable predicts an
independent variable. Granger’s original test regressed past values of the original
dependent variable and past values of the original independent variable on the
current value of the independent variable. Granger tests were performed using
AUTOREG procedure in SAS. Specifically, Granger tests were performed for
each time-series in the data set using a bivariate approach (Deephouse, 2000;
Leeflang and Wittink, 1992; McAlister, Srinivasan, and Kim, 2007): (1) the
firm’s corporate reputation and its marketing communication (advertising and
publicity) and (2) the firm’s corporate reputation and its financial performance
(dividend yield, market-to-book ratio, and profit).
Granger tests were not performed for all companies included in the study.
Since the purpose of this additional analysis is to ensure the results of the study,
reverse-causality tests were conducted for firms in which hypotheses were
supported. Table 9 presents the results of the Granger tests. Test results showed
that the coefficients for lagged corporate reputation were not significant in most
data sets. This implies that corporate reputation did not affect marketing
communication and financial performance.
138
Table 9
The Results of Granger Tests
Corporate Reputation
Company
Advertising
B
(S.E.)
American standard
Apple Computer
Publicity
B
(S.E.)
-0.0692
(0.4523)
Dividend Yield
B
(S.E.)
11.6879
(20.9542)
-0.0637
(0.2664)
AT&T
Coca Cola
Delta Air Lines
Fortune Brands
M/B Ratio
B
(S.E.)
0.3258
(0.6571)
0.3200
(0.3231)
2.7006
(0.7400)
0.1587
(0.2852)
-0.0060
(0.0107)
0.2451
(0.1273)
0.1494
(0.1358)
Kimberly Clark
Pfizer
0.4488
(0.3434)
-0.2270
(0.3727)
PPG Industries
483.2439
(258.0899)
199.3436
(45.6217)
-0.6687
(0.3289)
-0.5394
(0.2161)*
Stanley Works
Texas Instruments
United State
Tobacco
VF Corp.
0.0175
(0.0315)
1.6186
(6.5027)
Johnson & Johnson
Sara Lee
0.0775
(0.0658)
-19.1162
(15.1001)
Gillette
Proctor & Gamble
Profit
B
(S.E.)
256.2410
(28.1786)
0.0644
(0.0329)
-0.0831
(0.1645)
-0.0637
(0.2664)
-0.0260
(0.2081)
0.6918
(0.3654)
Vulcan Materials
* Significant at p < .05
139
The Effect of Sales Revenues
As with the effect of corporate reputation, alternative hypotheses that sales
revenue affects advertising, publicity, reputation, and R&D can be suggested.
These reverse causations were tested using Granger Walt tests for only firms that
exhibited a significant positive effect on sales revenue. Table 10 shows the results
of reverse causality tests. Test results showed that the coefficients for lagged sales
revenues were not significant in most data sets. It indicates that sales revenue did
not influence advertising, publicity, reputation, and R&D.
140
Table 10
The Results of Granger Tests
Sales Revenue
Company
American standard
Advertising
B
(S.E.)
0.005192
(0.001773)
Publicity
B
(S.E.)
Reputation
B
(S.E.)
R&D
B
(S.E.)
0.008163
(0.005765)
Apple Computer
AT&T
Coca Cola
0.0363
(0.006256)*
-0.002321
(0.0142)
-0.0309
(0.0177)
-0.000034
(0.0000259)
Delta Air Lines
Fortune Brands
Gillette
Johnson & Johnson
Kimberly Clark
Pfizer
0.0104
(0.0161)
0.1580
(0.0604)
0.0135
(0.007012)
0.0101
(0.003019)
0.000754
(0.0241)
0.0180
(0.0109)
0.0355
(0.0229)
-2.387E-6
(1.6482E-6)
PPG Industries
Proctor & Gamble
Sara Lee
0.0198
(0.0436)
0.0330
(0.0299)
-0.000183
(0.0000461)*
0.000630
(0.000470)
-0.0309
(0.0177)
Stanley Works
Texas Instruments
United State
Tobacco
VF Corp.
0.0363
(0.006256)
0.005057
(0.004465)
0.2354
(0.1147)
0.0109
(0.006141)
0.0122
(0.006505)
4.3038E-6
(3.2974E-6)
-0.000354
(0.000196)
0.0007422
(0.0207)
0.000439
(0.000220)
Vulcan Materials
* Significant at p < .05
141
-0.000968
(0.000502)
CHAPTER 6
DISCUSSION
As reviewed and hypothesized previously, significant positive
relationships between marketing communication and corporate reputation and
between marketing communication and sales revenue were expected. However,
the significant negative or non-significant relationships are surprising and notable.
This study provides a few possible explanations for these phenomena.
First, even though this study assumes a linear relationship between
marketing communication and corporate reputation or sales revenues, perhaps,
theoretically, marketing communication may have nonlinear influences on
corporate reputation or market performance. For example, diminishing returns
may exist. That is, an initial increase in marketing communication will enhance
corporate reputation or market performance, but beyond an optimal point, further
increases in marketing communication may be harmful. This finding has been
well-established in the advertising and sales relationship studies (Simom and
Arndt, 1980). Many economic models regarding the advertising and sales
relationship imply diminishing returns to increased advertising. No literature or
empirical study, however, has explored a nonlinear effect of marketing
communication on corporate reputation. Moreover, there has been no theoretical
142
framework or empirical study regarding a nonlinear effect or diminishing returns
of public relations efforts to market performance.
A recent study provides evidence that nonlinear relationships or
diminishing returns could be possible in explaining the presence of nonsignificant or negative relationships in the present study. Luo and Donthu (2006)2
found a curvilinear relationship with an inverted U-shape between marketing
communication productivity and shareholder value, suggesting that an
unrestricted increase in marketing communication productivity may be harmful
and cause negative market returns. Therefore, it could be possible that non-linear
relationships, such as diminishing returns or a s-shape response function, may
exist in the relationship between marketing communication and corporate
reputation or market performance. Further studies should examine the presence of
non-linear relationships.
A second possible explanation for the presence of non-significant or
negative influences of marketing communication on corporate reputation or sales
revenues is heterogeneity of the industries or product types of the firms included
2 Luo and Donthu (2006) define marketing communication productivity (MCP) as the conversion ratio
of marketing communication inputs (advertising media spending and sales promotion expenditures) to
outputs (sales level, sales growth, and corporate reputation). The logic of this approach is that firms
attempt to consume the least possible amount of inputs to achieve the same level of desired outputs
from time t to time t+1. If a firm cannot reduce its inputs without hurting its output level, it is
considered productive over time. Otherwise, it is unproductive and inefficient. The authors estimated
MCP using the dynamic Malmquist approach. To calculate MCP from time t to time t+1 for each firm,
Malmquist (1953) initially developed dynamic models to assess the total factor productivity of general
economic activities over time. Later, Fare and colleages (1992, 1994) constructed the time-series linear
programming Malmquist productivity index (for more details, see Luo and Donthu’s (2006) article).
143
in the sample. That is, industry category or product type could be one possible
explanation for these unexpected relationships. According to prior studies
(Blassubramanian and Kumar, 1990; Zinkhan and Cheng, 1992; Graham and
Frankenberger, 2000; Chan, Lakonishok, and Soughiannis, 2001; Mizik and
Jacobson, 2003), model estimates regarding marketing communication may be
different depending on the industry classification or product classification. In
general, for example, consumer products firms are believed to have a higher
advertising intensity than industrial products firms. Also, consumer products
firms typically have broad target markets and are more likely to rely on massmediated types of marketing communication, whereas business-to-business
product firms typically have more focused targets and are more likely to utilize
customized marketing communications.
Since companies included in this study are heterogeneous, it might be
useful to explore whether there are any different effects by type of firm. The 18
companies included in the study were classified into four categories based on the
industry and product type, as presented in Table 1. They consist of 10 consumer
products firms, 4 industrial products firms, 2 consumer and industrial products
firms, and 2 services firms. Table 11 presents a summary of findings by firm
classifications.
144
Table 11
Summary of Hypotheses Tests by Firm Classification
Consumer
Products Firm
(all: 10 firms)
Industrial
Products Firm
(all:4 firms)
Consumer/
Industrial Firm
(all: 2 firms)
Services
Firm
(all: 2 firms)
H1:
3(+), 5(-), 2(n.s.)
2(+), 2(n.s.)
2(n.s)
2(-)
Advertising
– Reputation
H2:
4(+), 2(-), 4(n.s.)
1(+), 3(n.s.)
1(+), 1(-)
2(n.s.)
Publicity
– Reputation
H3:
9 (+), 1(n.s.)
2(+), 2(n.s.)
1(+), 1(n.s.)
1(+)
Advertising
– Sales
H4:
2(+), 2(-), 6(n.s.)
1(+), 3(n.s.)
2(n.s.)
2(n.s.)
Publicity
– Sales
Note: Number before parenthesis refers to the number of firms with a relationship.
(+) refers to a positive relationship, (-) represents a negative relationship, and n.s.
indicates a non-significant relationship.
When examined in this context, advertising effects by firm’s classification
were obvious. The effect of advertising on sales was supported in most consumer
products firms, which is not surprising given a higher advertising investment and
the greater importance of advertising for consumer products firms than industrial
products firms. In services firms, even though some relationships were negative
(the advertising-reputation relationship), only advertising was significantly related
to corporate reputation and sales revenue. Publicity did not exhibit any significant
association to corporate reputation or sales revenues in services firms. This
finding is inconsistent with one’s expectation that products firms can better use
145
advertising to communicate products’ value to potential customers, whereas
service firms may need to use more reliable, credible media as communication
instruments for their services.
No specific pattern regarding the effect of publicity by a firm’s
classification was evident, except for the fact that publicity did not show any
significant relationship with corporate reputation or sales in services firms. That is,
no specific pattern by a firm’s classification was found in the relationship between
publicity and corporate reputation and between publicity and sales revenues.
However, it seems to be difficult to generalize these findings, because of the small
and convenient sample composition of this study. Details on the limitations of the
sample composition are discussed in the limitations and further study section.
Even though this study did not find any clear pattern based on a firm’s
classifications, further research that explores firm and/or industry specific effects
of marketing communication on corporate reputation or sales revenues may
uncover consistent findings.
Theoretical Implication
This is the first empirical study to use a multi-industry sample of firms
over a 21-year period to examine the idea that higher advertising and favorable
146
publicity generate favorable assessment of corporate reputation and increase sales
revenues. Also, this is the first study to attempt to examine the simultaneous
effect of advertising and publicity using longitudinal panel data at the firm level.
Additionally, this study suggests a new measure of publicity. Many prior
studies have examined the effect of publicity as measured as a positive or
negative manipulation of a news story in an experimental setting. Or, publicity
has been measured by the number of news stories, the volume of nonnegative
media coverage, or advertising equivalency. The measure of publicity used in this
study is not a newly developed method, but a new application. In this study,
publicity was measured as the extent to which media reports are favorable, using
the Janis-Fadner coefficient of imbalance (Janis and Fadner, 1965; [Equation 1]).
It measures the relative proportion of favorable to unfavorable news stories while
controlling for the overall volume of news stories. This method was initially
developed for analyzing wartime propaganda and has been used in strategy
research involving media to assess the degree of media favorability (Carroll,
2004; Deephouse, 2000; Pollock and Rindova, 2003). However, few studies have
used this method as a publicity measure of public relations. Because one of the
main purposes of public relations is to obtain favorable publicity from media, it
appears reasonable to use favorableness as a publicity measure.
147
Finally, this study includes accounting/financial (e.g., dividend yield,
market-to-book ratio, profitability) and strategy (e.g., diversification, focus of the
firm, R&D) factors in the corporate reputation model and the sales revenue model,
as well as marketing communication (advertising, publicity) variables. Also, firm
characteristics or contextual variables such as firm size controlled for the
relationship between marketing communication and corporate reputation or
market performance. Including alternate variables in the model could improve the
model’s accuracy. Furthermore, the positive impacts of marketing communication
on corporate reputation and sales revenues in the models with these many
variables imply that there may be an interaction effect of marketing
communication variables and financial/accounting/strategy variables in managing
corporate reputation or sales revenues. For example, the effect of marketing
communication on corporate reputation can differ depending on a firm’s strategy,
such as diversification or branding strategy. Further research that examines how
marketing communication and financial/accounting or strategy variables interact
with each other to improve corporate reputation and market performance would
be valuable to justify advertising expenditures and public relations efforts. These
further studies would be also useful for developing marketing communication
strategies.
148
Managerial Implications
The findings of this study also generate useful implications for managerial
considerations. The primary finding of this study appears to imply that a firm can
take advantage of advertising and publicity to achieve dual benefits, namely,
corporate reputation and sales revenues. Prior research has assessed the
accountability of marketing communication as mainly market or financial
performance output. This study stresses the impact of advertising and publicity on
corporate reputation, as well as their effect on market performance. A firm’s
marketing communication expenditures and efforts should be proven by its
customers (sales revenues). At the same time, however, it can also be supported
by the managerial community. It should be noted that the dependent measure,
corporate reputation, is an assessment by executives, directors, and financial
analysts. It implies that a firm’s marketing communication can affect a firm’s
reputation ranking in its industry, which comes from managerial properties. In
turn, reputation rankings (e.g., Fortune’s Most Admired American Corporations)
publicized through the media can be used as an evaluative criterion to form the
public’s attitude and opinion about the firm. Thus, the study’s findings that
advertising and publicity have a positive impact on corporate reputation as well as
149
sales revenues can be used to justify the accountability for marketing
communication efforts.
Although this study demonstrates that advertising and publicity have a
significant impact on corporate reputation and sales revenues for certain
companies, the overall results found through the time-series analysis for 18
companies are somewhat inconsistent with the prior expectations. Non-significant
or negative impacts of advertising and publicity on corporate reputation and sales
revenues occur for some companies. These findings suggest that advertising and
publicity may not be the most effective marketing communication tools for
managing corporate reputation and market performance. Also, these findings shed
light on the current trend of firms’ reliance on nontraditional marketing
communication.
In recent years, companies have experienced an increase in the number
and diversity of communications options to reach consumers. Traditional
advertising media have fragmented, and new, nontraditional media, promotion,
and other communication alternatives have emerged. Thus, many companies are
faced with the challenge of determining the best method of allocating marketing
communication dollars across not only the traditional media but also
nontraditional media, such as new media, social networking sites, database and
direct marketing, and word-of-mouth. Further studies that extend the present
150
study to include other nontraditional marketing communication activities would
be beneficial to marketing managers who determine the marketing
communication mix.
151
CHAPTER 7
CONCLUSION
The accountability of marketing communication expenditure or efforts has
long been a central issue. Many prior studies have concentrated on market
performance to assess the effectiveness of marketing communication. In spite of
the interest in new metrics of marketing communication effects, such as
shareholder value or systemic risk, market performance has still been of key
interest among marketing scholars and practitioners. In addition, recent
developments of the market-based assets theory (Srivastava, Shervani, and Fahey,
1998) focus on intangible market-based assets such as brand equity or corporate
reputation. The resource-based view of the firm proposes that a favorable
reputation is an intangible asset that increases a firm’s performance (Barney,
1991; Hall, 1992).
This study examines the impact of a firm’s advertising and publicity, two
important marketing communication activities, on its corporate reputation and
sales revenues. There is no doubt that advertising is an important marketing
communication tool. As media circumstances and the customers’ needs have
changed, however, traditional advertising struggles to catch consumers’ attention,
and public relations has been recognized as a vital marketing communication tool.
152
While a few studies have examined the effects of advertising and publicity at a
consumer attitude or behavior level, no attention has been given to the
simultaneous effects of advertising and publicity at the firm level. Furthermore,
there are few insights that relate advertising and publicity to corporate reputation.
Thus, advertising, publicity, corporate reputation and sales revenues are the main
interests of this study.
Two regression models were established for testing the hypotheses: (1) a
model for the marketing communication-corporate reputation relationship and (2)
a model for the marketing communication-sales revenue relationship.
For the marketing communication and corporate reputation relationship,
the major finding of this study is that advertising and publicity have significant
effects on corporate reputation for certain companies. Other variables, such as a
firm’s dividend yield to investors, market value, diversification, and profitability
were significantly related to assessments of corporate reputation for certain
companies, but the direction of the relationship varied from company to company.
For example, as expected, low dividend yields induce high assessments of
corporate reputation for certain companies. A firm’s current market value also
affects assessments of a firm’s reputation. More diversified companies yield
lower corporate reputations for certain companies.
153
Regarding the relationship between marketing communication and sales
revenues, the major finding is that advertising and publicity have significant
effects on sales revenues for some companies. A firm’s R&D expenditures, the
focus of the firm, and firm size also showed a significant positive relevance to
sales revenues for certain companies. Reputation, when included in the marketing
communication and sales model, exhibited a significant relationship to sales
revenues, but, contrary to expectations, the direction of the relationship differed
among companies in the sample.
Despite the contributions of the present study as discussed previously, it is
not free from limitations. This chapter points out this study’s limitations and
suggests further research directions.
Limitations and Future Research
First, it should be noted that the composition of the sample is a potential
limitation. Although it is a valid sample, the sample of this study is not truly
representative of the population of firms in the economy. Data limitation
constrained the focus of this study to firms that are large, publicly held companies.
The sample of this study was obtained from Fortune’s annual reputation survey of
the most admired U.S. corporations, which consisted of mostly large American
154
firms. Furthermore, this study limited the sample to only firms with available data
for the whole 21-year period. Thus, the representativeness and generalizability of
the findings are limited. The results cannot be generalized beyond relatively large
American firms without further investigation. Further research will be needed to
examine whether the relationship between advertising/publicity and corporate
reputation/sales holds under other conditions, such as a more general sample that
includes poorly performing firms or small firms. However, it was impossible to
include small-sized firms or poorly performing firms in this study since it was
difficult to obtain the necessary longitudinal data regarding these firms.
Second, although this study controlled for many accounting/financial,
strategy, and firm characteristic variables, other variables not included in the
model may impact the relationship between marketing communication and
corporate reputation and between marketing communication and market
performance. For example, non-economic variables, such as a firm’s social
responsibility and charitable donations, or industry competition effects, may
influence judgments about the firm or market performance. Further research that
includes the effects of historical performance measures rather than short-term
performance, non-economic measures, and a firm’s brand level strategy on
corporate reputation and market performance would be valuable
155
The third limitation is found in the measure of publicity. Even though this
study measured publicity in a new way, in measuring publicity with content
analysis, the data included only two daily newspapers (The New York Times and
Wall Street Journal). The selection of these two daily newspapers is based on the
fact that they have been frequently used in many prior studies and that they have
the largest circulation among U.S. newspapers. However, including other media
sources, such as news wire services or broadcast media, may improve the
specificity of the analyses or measurement accuracy and increase our
understanding of publicity measure.
More importantly, there may be a concern that publicity is a weak measure
of public relations (PR). Publicity may not represent the whole spectrum of PR
activities. In contrast to the advertising measurement in terms of dollar spending,
there has been no agreement on the best way to measure and quantify PR. PR has
been measured by counting the number of news releases, the number of column
inches, coverage in specific publications, and so on. PR does not provide any
measurable numbers at all.
The absence of the method to measure PR appears to be attributable to the
different orientations and definitions of PR. Among PR scholars and professionals,
PR has been viewed as the management function that establishes and maintains a
mutually beneficial relationship between an organization and the various
156
stakeholders (Cutlip, Center, and Broom, 1985; Dozier and Broom, 1995;
Lindenmann et. al., 1997). Among advertising and marketing scholars, however,
PR is still perceived as a set of technical tools, such as publicity and media
relationship, intended to support marketing goals. In recent years, a few PR
scholars (Grunig and Grunig, 1998; Harris, 1999) have distinguished corporate
public relations (CPR) and marketing public relations (MPR). MPR is recognized
as one of several marketing activities intended to support the relationships
customers have with a brand and company. They include all non-traditional
marketing communications, other than advertising. CPR is seen as having much
broader communication management functions than MPR. Beyond the marketing
function, CPR emphasizes all communication activities for building a good
relationship with various stakeholders surrounding an organization, such as
shareholders, employees, suppliers, communities, and governments, as well as
customers. These different orientations of PR may make it difficult to measure PR
in a standardized way.
In order to develop a measure of PR that could theoretically represent the
whole spectrum of PR activity, it is important to go beyond the idea of advertising
and PR as different disciplines with different perspectives and find a way for
various marketing communications to interact with each other to improve the
overall value of a firm. A focus group or in-depth interview with PR/advertising
157
professionals would be helpful to develop a theoretical framework for finding the
most effective PR measurement for a firm. Technically, systematic data
management regarding PR activities will provide a basis for quantifying PR.
Tasks to identify PR as a revenue generator have become important. However, PR
measurement is more than the barometer of PR success, and PR success is
impossible without measurement. Thus, qualifying PR activity is a primary issue
for further marketing communication research development.
For future study, an alternative measure of corporate reputation is
suggested. Corporate reputation of this study was derived from Fortune’s
reputation score, which came from firms’ executives, directors, and financial
analysts. Despite many prior studies having successfully used Fortune’s corporate
reputation score in both marketing and strategy studies, their focus may be
different from other stakeholders of a firm, such as customers or media. Thus, the
use of an alternative measure of corporate reputation from other stakeholders may
provide different results and implications. For example, The Reputation Institute
has created an overall reputation score called the Reputation Quotient (RQ,
Fombrun, 1996) from the general U.S. population. To create the RQ score,
respondents are asked to nominate firms they consider to have the best and worst
reputations in the country and then provide a 20-item evaluation of the reputation
of each firm. This RQ score can be used as an alternative measure of corporate
158
reputation ascribed to firms by general consumers. The methodology used to
create RQ reputation scores by The Reputation Institute is presented in Appendix
D. Further research should examine the firm’s reputation from the perspective of
different stakeholders.
The present study did not use normalized data of the variables because of
the lack of data. For example, to normalize variables, one first calculates industry
medians for the variables. Then, one normalizes each firm’s data relative to the
respective industry medians by subtracting the median values of the firms’
corresponding industry groups. If data is available, normalization of the variables
will make it possible to account for any systematic differences between industry
groups and to investigate their relative importance by comparing estimates.
The results of this study imply the presence of the interaction or
moderating effect of variables. Two interaction effects are suggested for further
study: (1) the interaction of advertising and publicity on corporate reputation and
market performance and (2) the interaction effect of corporate reputation and
marketing communication on market performance.
First of all, the interaction of advertising and publicity can be expected.
For methodological reasons, this study examined the main effect of advertising
and publicity. The inclusion of interactions in the regression model, despite the
study not being specifically designed to assess the interaction, can make it
159
difficult to estimate the other effects in the model. Thus, this study did not include
the interaction effect of advertising and publicity so that other effects might be
better assessed. However, sometimes the way advertising influences corporate
reputation may depend on publicity. For example, firms with high advertising
expenditures may build higher corporate reputations from favorable media
coverage. Also, in judging corporate reputation or generating sales revenues, the
reliance on publicity may increase when the confidence in advertising generated
by a firm is absent. The descriptive analysis presented in Figures 13 and 14
supports this idea that there might be an interaction effect of advertising and
publicity on sales revenues. The results of the descriptive analysis suggest that if
the publicity condition is the same (unfavorable publicity or favorable publicity),
firms that spend more on advertising (high advertising expenditures) generate
much higher sales revenues. Thus, further studies that examine the interaction
effect of advertising and publicity on corporate reputation or market performance
in greater detail are necessary. Moreover, theoretical research using qualitative
methods (e.g., in-depth interview, field studies, focus groups) to develop a
conceptual framework and theoretical proposition of how advertising and PR
work together would be useful for setting a future research agenda.
Second, the findings regarding the relationship between corporate
reputation and sales revenues suggest another interesting issue for further
160
investigation: how corporate reputation moderates the relationship between
marketing communication and market performance. This study focused on the
main effects of marketing communication on corporate reputation and sales
revenue, respectively. For examining the relationship between marketing
communication and sales revenue, corporate reputation was used as one of the
control variables to rule out the influence of any other effect on sales revenues
other than marketing communication effects. It found the main effects of
marketing communication on corporate reputation and sales revenue. Also, the
main effect of corporate reputation on sales revenue was found for certain
companies. On the basis of these findings, one can assume that the relationship
between marketing communication and market performance can be influenced by
corporate reputation.
Specifically, prior brand equity studies appear to provide a theoretical
framework for a moderating role of corporate reputation on the relationship
between advertising and market performance. Many academic studies have
revealed that marketing activities influence brand equity. In marketing literature,
it is widely accepted that advertising increases brand equity (Aaker and Biel, 1993,
Kirmani and Zeithaml, 1993; Mela, Gupta, and Lehmann, 1997). Brand equity
influences sales directly by means of consumer choice, and indirectly by
enhancing the effectiveness of the brand’s marketing efforts and insulating the
161
brand from competitive activity (Keller, 2003). This idea can be applied to the
study of corporate reputation, in that reputation has the same conceptual
association as brand equity. Based on well-known previous research regarding the
role of brand equity on the advertising and market performance relationships, one
can imagine that the incremental value that consumers give to a well-respected
company will be greater than for an equivalent less-respected company. Thus,
further studies can investigate how corporate reputation reinforces the impact of
advertising in enhancing market performance (the moderating role of corporate
reputation on the relationship between advertising and market performance).
Corporate reputation can also moderate the effect of publicity on market
performance. As discussed in the hypotheses test section, the contribution of
publicity to market performance may be measured by examining the moderating
role of corporate reputation on market performance. As public relations scholars
and practitioners insist, if public relations contributes to a firm’s market
performance by achieving public relations’ goals of building corporate reputation
or goodwill, the strength of the relationship between publicity and market
performance will increase as corporate reputation increases. Thus, further studies
that investigate how corporate reputation moderates the relationship between
public relations and market performance would be useful to measure the
contribution of public relations to market performance. The author hopes the
162
findings of the present study will be a solid basis for investigating how corporate
reputation interacts with other marketing communication activities to affect a
firm’s market performance.
Finally, this study provides new research ideas for more thoroughly
exploring the contribution of corporate reputation to market performance. Unlike
prior studies that demonstrated the positive effect of corporate reputation on
market performance, the positive relationship was not strongly supported by the
current study, as shown in Table 5. Prior studies seem to provide a reason for the
unexpected relationship between corporate reputation and sales revenues.
Boulstridge and Carrigan (2000) and Page and Fearn (2005) suggested that
corporate reputation is recognized as important to most consumers, but consumers
do not think that corporate reputation is particularly important when making a
buying decision. Page and Fearn (2005) found that 70% of consumers in the UK,
64% in the U.S., and 65% in Japan did not think about corporate reputation while
they were shopping. These prior studies imply that there might be an alternative
measure other than sales revenue to explore the contribution of corporate
reputation to market performance. Thus, further research that considers an
alternative measure of market performance may provide more robust findings.
In addition, in order for corporate reputation to play an important role in
influencing buying decisions, customers need to link the products they are
163
considering with the company. However, there are some companies that have a
different name than their major brands. That is, the effect of corporate reputation
on sales revenue can differ depending on a firm’s branding strategy3. For example,
corporate branding strategy makes it easy to be aware of the link between a
company name and brand name, but mixed branding or house of brands strategies
may make it difficult to link the company name and brand name. This study failed
to consider the branding strategy factor because of the data availability. It was
difficult to obtain firms’ complete brand level data for a 21-year period. For
example, firms’ mergers and acquisitions made it difficult to define and obtain
firms’ branding strategy variable for each year. When data was examined
regarding the effect of brand strategy based on the information from companies as
of 2005 (18 firms included in this study use different branding strategies. Among
them, 11 firms employ mixed branding or house of brands strategies); no clear
pattern was found regarding the relationship between corporate reputation and
sales revenue. However, it appears to be natural for the composition of the sample
in this study. Further studies that include the brand-level data would more
3 On the basis of a comprehensive content analysis of brands of major U.S. and European grocery
products, Laforet and Saunders (1994) propose three categories of brands based on the use of the firm’s
name in products’ brand names: (1) corporate branding: the name of the firm or its subsidiary is
prominent in the brand names of the products or services (e.g., AT&T, Apple Computer); (2) mixed
branding: a firm’s name is combined with another name (e.g., Gillette’s Gillette, Oral-B, Duracell,
Braun, Waterman); (3) house of brands: a firm’s name is not used at all to mark products or services
(e.g., Procter & Gamble’s Pampers, Crest, Tide, Bounty, Febreze) (Rao, Agarwal, Dahlhoff, 2004).
164
thoroughly explore the contribution of corporate reputation to market
performance.
165
Appendix A
HOW FORTUNE CONDUCTS THE MOST ADMIRED SURVEY
The Most Admired list is the definitive report card on corporate reputations. Our
survey partners at Hay Group started with the FORTUNE 1,000 -- the 1,000
largest U.S. companies ranked by revenue -- and the top foreign companies
operating in the U.S. They sorted the companies by industry and selected the ten
largest companies in each.
To create the 65 industry lists, Hay asked executives, directors, and analysts to
rate companies in their own industry on eight criteria, from investment value to
social responsibility. This year only the best are listed as most admired: A
company's score must rank in the top half of its industry survey. Ranks for the rest
of the contenders are available online only.
To create the top 20 and overall list of Most Admired Companies, Hay Group
asked the 10,000 executives, directors, and securities analysts who had responded
to the industry surveys to select the ten companies they admired most. They chose
from a list made up of the companies that ranked among the top 25% in last year's
survey, plus those that finished in the top 20% of their industry. Anyone could
vote for any company in any industry. The difference in the voting rolls is why
some results can seem anomalous -- for example, FedEx is one of the top ten
Most Admired Companies but only second in its own industry.
A total of 611 companies in 70 industries were surveyed. Due to an insufficient
response rate, the results for 29 companies in five industries are not reported:
advertising, consumer credit, health care, pharmacy and other services, precision
equipment, and printing. Thus American Express (No. 17) and 3M (No. 20) are
on the overall list even though their industries -- consumer credit and precision
equipment -- did not have enough responses to merit a category.
Source: Fortune Magazine, Vol. 153, No. 4, March 6, 2006
166
Appendix B
VISUAL INFORMATION
(ADVERTISING, PUBLICITY, AND CORPORATE REPUTATION)
Advertising
Publicity
20
05
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
American Standard (1985-2005)
Reputation
Note: in case of publicity, above the line (+) refers to favorable publicity and below
the line (-) refers to unfavorable publicity.
Advertising
5
20
0
3
20
0
1
9
Publicity
20
0
19
9
19
9
7
5
19
9
3
19
9
1
19
9
9
19
8
7
19
8
19
8
5
AT&T (1985-2005)
Reputation
Note: in case of publicity, above the line (+) refers to favorable publicity and below
the line (-) refers to unfavorable publicity.
167
Advertising
Publicity
20
05
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
Apple Computer (1985-2005)
Reputation
Note: in case of publicity, above the line (+) refers to favorable publicity and below
the line (-) refers to unfavorable publicity.
Advertising
Publicity
20
05
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
Coca Cola (1985-2005)
Reputation
Note: in case of publicity, above the line (+) refers to favorable publicity and below
the line (-) refers to unfavorable publicity.
168
Advertising
Publicity
20
05
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
Delta Air Lines (1985-2005)
Reputation
Note: in case of publicity, above the line (+) refers to favorable publicity and below
the line (-) refers to unfavorable publicity.
Advertising
Publicity
20
05
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
Fortune Brands (1985-2005)
Reputation
Note: in case of publicity, above the line (+) refers to favorable publicity and below
the line (-) refers to unfavorable publicity.
169
Advertising
Publicity
20
05
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
Gillette (1985-2005)
Reputation
Note: in case of publicity, above the line (+) refers to favorable publicity and below
the line (-) refers to unfavorable publicity.
Advertising
Publicity
20
05
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
Johnson & Johnson (1985-2005)
Reputation
Note: in case of publicity, above the line (+) refers to favorable publicity and below
the line (-) refers to unfavorable publicity.
170
Advertising
Publicity
20
05
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
Kimberly Clark (1985-2005)
Reputation
Note: in case of publicity, above the line (+) refers to favorable publicity and below
the line (-) refers to unfavorable publicity.
Advertising
Publicity
20
05
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
PPG Industries (1985-2005)
Reputation
Note: in case of publicity, above the line (+) refers to favorable publicity and below
the line (-) refers to unfavorable publicity.
171
Advertising
Publicity
20
05
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
Pfizer (1985-2005)
Reputation
Note: in case of publicity, above the line (+) refers to favorable publicity and below
the line (-) refers to unfavorable publicity.
Advertising
Publicity
20
05
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
Proctor & Gamble (1985-2005)
Reputation
Note: in case of publicity, above the line (+) refers to favorable publicity and below
the line (-) refers to unfavorable publicity.
172
Advertising
Publicity
20
05
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
Sara Lee (1985-2005)
Reputation
Note: in case of publicity, above the line (+) refers to favorable publicity and below
the line (-) refers to unfavorable publicity.
Advertising
Publicity
20
05
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
Stanley Works (1985-2005)
Reputation
Note: in case of publicity, above the line (+) refers to favorable publicity and below
the line (-) refers to unfavorable publicity.
173
Advertising
Publicity
20
05
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
Texas Instruments (1985-2005)
Reputation
Note: in case of publicity, above the line (+) refers to favorable publicity and below
the line (-) refers to unfavorable publicity.
Advertising
Publicity
20
05
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
United States Tobacco (1985-2005)
Reputation
Note: in case of publicity, above the line (+) refers to favorable publicity and below
the line (-) refers to unfavorable publicity.
174
Advertising
Publicity
20
05
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
VF Corp. (1985-2005)
Reputation
Note: in case of publicity, above the line (+) refers to favorable publicity and below
the line (-) refers to unfavorable publicity.
Advertising
Publicity
20
05
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
Vulcan Materials (1985-2005)
Reputation
Note: in case of publicity, above the line (+) refers to favorable publicity and below
the line (-) refers to unfavorable publicity.
175
Appendix B (Cont)
VISUAL INFORMATION
(ADVERTISING, PUBLICITY, AND CORPORATE REPUTATION)
American Standard (1985-2005)
1985
1987
1989
1991
1993
Advertising
1995
1997
1999
Publicity
2001
2003
2005
Sales
Note: in case of publicity, above the line (+) refers to favorable publicity and below
the line (-) refers to unfavorable publicity.
AT&T (1985-2005)
1985
1987
1989
1991
1993
Advertising
1995
1997
Publicity
1999
2001
2003
2005
Sales
Note: in case of publicity, above the line (+) refers to favorable publicity and below
the line (-) refers to unfavorable publicity.
176
Apple Computer (1985-2005)
1985
1987
1989
1991
1993
1995
Advertising
1997
1999
Publicity
2001
2003
2005
Sales
Note: in case of publicity, above the line (+) refers to favorable publicity and below
the line (-) refers to unfavorable publicity.
Advertising
Publicity
20
05
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
Coca Cola (1985-2005)
Sales
Note: in case of publicity, above the line (+) refers to favorable publicity and below
the line (-) refers to unfavorable publicity.
177
Advertising
Publicity
20
05
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
Delta Air Lines (1985-2005)
Sales
Note: in case of publicity, above the line (+) refers to favorable publicity and below
the line (-) refers to unfavorable publicity.
Advertising
Publicity
20
05
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
Fortune Brands (1985-2005)
Sales
Note: in case of publicity, above the line (+) refers to favorable publicity and below
the line (-) refers to unfavorable publicity.
178
Advertising
Publicity
20
05
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
Gillette (1985-2005)
Sales
Note: in case of publicity, above the line (+) refers to favorable publicity and below
the line (-) refers to unfavorable publicity.
Advertising
Publicity
20
05
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
Johnson & Johnson (1985-2005)
Sales
Note: in case of publicity, above the line (+) refers to favorable publicity and below
the line (-) refers to unfavorable publicity.
179
Advertising
Publicity
20
05
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
Kimberly Clark (1985-2005)
Sales
Note: in case of publicity, above the line (+) refers to favorable publicity and below
the line (-) refers to unfavorable publicity.
Advertising
Publicity
20
05
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
PPG Industries (1985-2005)
Sales
Note: in case of publicity, above the line (+) refers to favorable publicity and below
the line (-) refers to unfavorable publicity.
180
Advertising
Publicity
20
05
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
Pfizer (1985-2005)
Sales
Note: in case of publicity, above the line (+) refers to favorable publicity and below
the line (-) refers to unfavorable publicity.
Advertising
Publicity
20
05
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
Procter & Gamble (1985-2005)
Sales
Note: in case of publicity, above the line (+) refers to favorable publicity and below
the line (-) refers to unfavorable publicity.
181
Publicity
Advertising
20
05
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
Sara Lee (1985-2005)
Sales
Note: in case of publicity, above the line (+) refers to favorable publicity and below
the line (-) refers to unfavorable publicity.
Advertising
Publicity
20
05
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
Stanley Works (1985-2005)
Sales
Note: in case of publicity, above the line (+) refers to favorable publicity and below
the line (-) refers to unfavorable publicity.
182
Advertising
Publicity
20
05
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
Texas Instruments (1985-2005)
Sales
Note: in case of publicity, above the line (+) refers to favorable publicity and below
the line (-) refers to unfavorable publicity.
Advertising
Publicity
20
05
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
United States Tobacco (1985-2005)
Sales
Note: in case of publicity, above the line (+) refers to favorable publicity and below
the line (-) refers to unfavorable publicity.
183
Advertising
Publicity
20
05
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
VF Corp. (1985-2005)
Sales
Note: in case of publicity, above the line (+) refers to favorable publicity and below
the line (-) refers to unfavorable publicity.
Advertising
Publicity
20
05
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
Vulcan Materials (1985-2005)
Sales
Note: in case of publicity, above the line (+) refers to favorable publicity and below
the line (-) refers to unfavorable publicity.
184
Appendix C
DATA TRANSFORMATION
Data Transformations for Corporate Reputation Model
CRit = α + B1 ADit-1 + B2 PBit + B3 DYt + B4 MBit + B5 DVit-1 + B6 PFit-1 + B7 FSit + eit
Company
American Standard
AT&T
Apple Computer
Coca Cola
Delta Air Lines
Fortune Brands
Gillette
Johnson & Johnson
Kimberly Clark
PPG Industries
Pfizer
Procter & Gamble
Sara Lee
Stanley Works
Texas Instruments
UST Inc.
VF Corp.
Vulcan Materials
Advertising
Publicity
M/B Ratio
Diversification
Profit
Firm Size
Original
Dividend
Yield
Original
Logarithmic
Logarithmic
Original
Original
Logarithmic
Logarithmic
Original
Original
Logarithmic
Original
Original
Original
Original
Original
Original
Original
Original
Original
Original
Original
Original
Original
Original
Original
Original
Original
Original
Original
Original
Original
Original
Original
Original
Original
Logarithmic
Original
Original
Original
Original
Original
Original
Logarithmic
Logarithmic
Original/log
Original
Original
Original
Original
Original
Logarithmic
Original
Original
Original
Original
Original
Original
Original
Original
Original
Original
Logarithmic
Logarithmic
Original
Original
Original
Original
Logarithmic
Logarithmic
Logarithmic
Logarithmic
Original
Original
Original
Original
Original
Logarithmic
Original
Logarithmic
Original
Original
Original
Original
Original
Original
Original
Original
Original
Logarithmic
Original
Original
Original
Original
Original
Logarithmic
Original
Original
Original
Original
Original
Original
Original
Original
Original
Original
Original
Original
Original
Original
Original
Original
Original
Logarithmic
Original
Original
Original
Original
Original
Original
Original
Original
Original
Original
Original
Logarithmic
185
Data Transformation for Sales Revenue Model
SRit = α + B1 ADit-1 + B2 PBit + B3 CRit-1 + B4 RDit-1 + B5 FFit + B6 FSit + eit
Company
Advertising
Publicity
R&D
Focus of the Firm
Firm Size
Original
Original
Original
Original
Original
American Standard
Original
Original
Original
Original
Original
AT&T
Logarithmic
Original
Original
Original
Logarithmic
Apple Computer
Original
Original
Original
Original
Logarithmic
Coca Cola
Original
Original
Logarithmic
Original
Logarithmic
Delta Air Lines
Logarithmic
Original
Original
Logarithmic
Original
Fortune Brands
Original
Original
Original
Logarithmic
Logarithmic
Gillette
Logarithmic
Logarithmic
Original
Original
Original
Johnson & Johnson
Original
Original
Logarithmic
Original
Original
Kimberly Clark
Logarithmic
Logarithmic
Original
Original
Original
PPG Industries
Logarithmic
Original
Original
Original
Original
Pfizer
Original
Original
Original
Original
Original
Procter & Gamble
Original
Original
Original
Original
Original
Sara Lee
Logarithmic
Original
Original
Original
Original
Stanley Works
Original
Original
Original
Original
Logarithmic
Texas Instruments
Original
Original
Original
Original
Original
UST Inc.
Original
Logarithmic
Original
Original
Original
VF Corp.
Original
Original
Original
Original
Original
Vulcan Materials
2
Note: Data transformation was determined in terms of the increase in R and the redistribution of points along both sides of the fit
line.
186
Appendix D
SURBEY METHODOLOGY – THE REPUTATION INSTITUTE
The study was carried out in two phases: a nominations phase, from March to
June, 2005, and a ratings phase, from Aug. 30 to Sept. 26, 2005.
In the nominations phase, Harris Interactive conducted 6,977 interviews
throughout the U.S., using a combined online and telephone methodology. The
online respondents were randomly selected from the Harris Interactive online
panel. All respondents were asked to nominate two companies that they feel have
the best reputations overall and two companies that they feel have the worst
reputations overall. Nominations were open-ended, and all responses were tallied,
placing subsidiaries and brand names within the parent company.
By totaling the mentions for best and worst companies provided during the
nominations phase, Harris Interactive identified the list of 60 most visible
companies in the U.S. to be measured in the ratings phase.
In the ratings phase, 19,564 respondents were randomly selected to complete a
detailed rating of one or two companies with which they were "very or somewhat
familiar." All interviews were conducted online. Respondents rated companies on
20 attributes in the six key dimensions of the Harris-Fombrun Reputation
Quotient (RQ), including products and services, financial performance, workplace
environment, social responsibility, vision and leadership, and emotional appeal.
After the first company rating was completed, a respondent was given the option
to rate a second company.
Each of the 60 companies was rated by at least 253 people; the average number of
respondents per company was 650. All data were weighted to be representative of
the U.S. adult population. Weighting variables for this study included
demographic variables (i.e., age, sex, education, race, ethnicity, household income
and region) and some non-demographic variables to project findings to the U.S.
adult population.
Finally, reputation quotient (RQ) figures were calculated for each company to
determine the rankings. Each company's RQ is based on the respondents' ratings
of each company on the 20 attributes. RQs are calculated by summing the ratings
187
on the individual RQ attributes, dividing by the total possible score (i.e., 7 x the
total number of attributes answered) and multiplying by 100. The highest possible
score is 100. In comparing any two RQ scores, a t-test was used to determine
statistically significant differences at a confidence level of 95%.
Source: http://www.reputationinstitute.com/main/home.php
188
References
Aaker, David A. (1991), Managing Brand Equity, New York: The Free Press.
Aaker, David A. (1995), “Building Strong Brands,” Brandweek, 36(37), 28-33.
Aaker, David A. and Alexander L. Biel (1993), “Brand Equity and Advertising:
An Overview,” in Brand Equity and Advertising: Advertising’s Role in
Building Strong Brands, David A. Aaker and Alexander L. Biel, eds.
Hillsdale, NJ: Lawrence Erlbaum Associates, 1-10.
Aaker, David A. and Kevin L. Keller (1993), “Consumer Evaluations of Brand
Extensions,” Journal of Marketing, 54 (January), 27-41.
Ailawadi, Kusum L., Paul W. Farris, and Mark E. Parry (1994), “Share and
Growth Are Not Good Indicators of the Advertising and Sales/Promotion
Ratio,” Journal of Marketing, 58 (January), 86-97.
Ailawadi, Kusum, L., Donald R. Lehmann, and Scott A. Neslin (2003), “Market
Response to a Major Policy Change in the Marketing Mix: Learning from
P&G’s Value Pricing Strategy,” Journal of Marketing, 65 (January), 44-61.
Ailawadi, Kusum, L., Donald R. Lehmann, and Scott A. Neslin (2003), “Revenue
Premium as an Outcome Measure of Brand Equity,” Journal of Marketing,
67(October), 1-17.
Agres, S.J. and T. M. Dubitsky (1996), “Changing Needs for Brands,” Journal of
Advertising Research, 36(1), 21-31.
Argenti, P.A. (2003), Identity, Image, and Reputation in Corporate
Communication, New York: McGraw Hill/Irwin, 57-78
Assmus, Gert, John U. Farley, and Donald R. Lehman (1984), “How Advertising
Affects Sales: Meta-Analysis of Econometric Results,” Journal of
Marketing Research, 21 (February), 65-74.
Baldinger, Allen L. (1990), “Defining and Applying the Brand Equity Concept:
189
Why the Researcher Should Care,” Journal of Advertising Research, 30
(June/July), RC2-RC5.
Barney, J. (1991), “Firm Resources and Sustained Competitive Advantage,”
Journal of Management, 17, 99-120.
Baron, Reuben M. and David A. Kenny (1986), “The Moderator-Mediator
Variable Distinction in Social Psychological Research: Conceptual,
Strategic, and Statistical Considerations,” Journal of Psychology and
Social Psychology, 51(6), 1173-1182.
Bass, Frank M and Darral G. Clarke (1972), “Testing Distributed Lag Models of
Advertising Effects,” Journal of Marketing Research, 9 (August), 298-308.
Bass, Frank M. (1969), “A Simultaneous Equation Regression Study of
Advertising and Sales of cigarettes,” Journal of Marketing Research, 6
(August), 291-300.
Batra, Rajeev, Meyers, John, and Aaker, David (1996), Advertising
Management,5th ed, Upper Saddle River, NJ: Prentice Hall.
Beatty, Rondolph P. and Jay R. Ritter (1986), “Investment Banking, Reputation,
and The Underpricing of Initial Public Offerings,” Journal of Financial
Economics, 15 (1/2), 213-232.
Blackston, Max (1992), “Observations: Building Brand Equity by Managing the
Brand’s Relationships,” Journal of Advertising Research, 32 (May/June),
79-83.
Blasubramanian, Siva K. and V Kumar (1990), “Analyzing Variations in
Advertising and Promotional Expenditures: Key Correlates in Consumer,
Industrial, and Service Markets,” Journal of Marketing, 54 (April), 57-68.
Boulding, Williams and Richard Staelin (1993), “A Look on the Cost Side:
Market Share and Competitive Environment,” Marketing Science, 12
(Spring), 144-166.
Boulstridge, E., and Marylyn Carrigan (2000), “Do Consumers Really Care about
Corporate Responsibility? Highlighting the Attitude-Behavior Gap,”
Journal of Communication Management, 4(4), 355-368.
190
Bromley, Dennis Basil. (1993), Reputation, Image, and Impression Management.
NY:Wiley & Sons.
Broniaeczyk, Susan M. and Josep W. Alba (1994), “The Importance of the Brand
in Brand Extensions,” Journal of Marketing Research, 31 (May), 214-228.
Brown, Steven P. (1995), “The Moderating Effects of Insupplier/Outsupplier
Status on Organizational Buyer Attitudes,” Journal of the Academy of
Marketing Science, 23 (Summer), 170-182.
Brown, N., and C Deegan (1998), “The Public Disclosure of Environmental
Performance Information – a Dual Test of Media Agenda Setting Theory
and Legitimacy Theory,” Accounting and Business Research, 29, 21-41.
Burt, Ronald. (1983), Corporate Profits and Cooptation. NY: Academic Press.
Cable, John (1972), “Market Structure, Advertising Policy, and Intermarket
Differences in Advertising Intensity,” in Marketing Structure and
Corporate Behavior, Keith Cowling, ed. London: The Macmillan Press,
Ltd., 107-124.
Cameron, Glen T. (1994), “Does Publicity Outperform Advertising? An
Experimental Test of the Third-Party Endorsement,” Journal of Public
Relations Research, 6(3), 185-207.
Campbell, C. B. (1993), “Does Public Relations Affect the Bottom Line? Study
Shows CEOs Think So,” Public Relations Journal, 49 (10), 14-17
Campbell, J. P. (1977), On the Nature of Organizational Effectiveness, in P.S.
Coodman and J.M. Pennings eds. New Perspectives on Organizational
Effectiveness, (pp. 235-248), San Francisco: Jossey-Bass.
Campbell, Margaret C. (1999), “Perceptions of Price Unfairness: Antecedents and
Consequences,” Journal of Marketing Research, 36(2) 187-199.
Capon, Noel, John U. Farley, and Scott Hoenig (1990), “Determinants of
Financial Performance: A Meta Analysis,” Management Science, 36
(October), 1143-1159.
191
Carlson, Les, Stephen J. Grove, Russell N. Lacsniak, and Norman Kangun (1996),
“Does Environmental Advertising Reflect Integrated Marketing
Communications? An Empirical Investigation,” Journal of Business
Research,” 37(3), 225-232.
Carroll, Craig, and McCombs, Maxwell. (2003), “Agenda-Setting Effects of
Business News on the Public’s Images and Opinions about Major
Corporations,” Corporate Reputation Review, 6(1), 36-46.
Chang, Yuhmiin, and Esther Thorson (2004), “Television and Web Advertising
Synergies,” Journal of Advertising, 33 (2), 75-84
Chauduhuri, Arjun (2002), “How Brand Reputation Affects the AdvertisingBrand Equity Link,” Journal of Advertising Research, May/June, 33-43.
Chauduhuri, Arjun and Morris B. Holbrook (2001), “The Chain of Effects from
Brand Trust and Brand Affect to Brand Performance: The Role of Brand
Loyalty,” Journal of Marketing, 65(April), 81-93.
Chow, G. (1960), “Test of Equality between Sets of Coefficients in Tow Linear
Regressions,” Economeritca, 28, 591-604.
Chen, C. C. and J. R. Meindl (1991), “The Construction of Leadership Images in
the Popular Press: The Case of Donald Burr and People Express,”
Administrative Science Quarterly, 36, 521-551.
Comanor, Williams S. and Thomas A. Wilson (1974), Advertising and Market
Power, Cambridge, MA: Harvard University Press.
Confer, Marian E. (1992), “The Media Multiplier: Nine Studies Conducted in
Seven Countries,” Journal of Advertising Research, 32(1), RC4-RC10.
Confer, Marian E. and Donald McGlathery (1991), “The Research Study: The
Advertising Impact of Magazines in Conjuction with Television,” Journal
of Advertising Research, 31(1), RC2-RC5.
Cook, William A. (1996), “Paradise Tossed,” Journal of Advertising Research, 36
(March/April), 6-7.
192
Day, George S. and Wensley, Robin (1988), “Assessing Advantage: A
Framework for Diagnosing Competitive Superiority,” Journal of Marketing, 52(1),
1-20.
Deephouse, D. L. (2000), “Media Reputation as a Strategic Resource: An
Integration of Mass Communication and Resource-Based Theories,”
Journal of Management, 26(6), 1091-1112.
Dekimper, Marnik G. and Dominique M. Hanssens (1995), “The Persistence of
Marketing Effects on Sales,” Marketing Science, 14 (Winter), 1-21.
Defleur, M. L., L. Davenport, M. Cronin, and M Defleur (1992), “Audience
Recall of News Stories Presented by Newspaper, Computer, Television,
and Radio,” Journalism Quarterly, 69, 1010-1022.
Dierickx, Ingemar and Cool, Karel (1989), “Asset Stock Accumulation and
Sustainable Competitive Advantage,” Management Science, 35, 15041511.
Dollinger, Marc J., Golden, Peggy A., and Saxton, Todd (1997), “The Effect of
Reputation on the Decision to Joint Venture,” Strategic Management
Journal, 18(2), 127-140.
Duncan, Thomas R. and S. Moriarty (1997), Driving Brand Value, New York:
McGraw Hill.
Duncan, Thomas R. and Stephen E. Everett (1993), “Client Perceptions of
Integrated Marketing Communications,” Journal of Advertising Research,
37(3), 30-39.
Durbin, J. (1970), Testing for Serial Correlation in Least-Square Regression
When Some of the Regressors are Lagged Dependent Variables,”
Econometrica, 38, 410-421.
Dutta, Shantanu, Om Narasimhan, and Surendra Rajiv (1999), “Success in HighTechnology Markets: Is Marketing Capability Critical?” Marketing
Science, 18(4), 547-568.
Dutton, J. and J. Dukerich (1991), “Keeping an Eye on the Mirror: The Role of
193
Image and Identity in Organizational Adaptation,” Academy of
Management Journal, 34, 517-554.
Eagle, Lynne and Philip Kitchen (2000), “Building Brands or Bolstering Egos? A
Comparative Review of the Impact and Measurement of Advertising on
Brand Equity,” Journal of Marketing Communications, 6, 91-106.
Eagle, Lynne and Philip Kitchen, Ken Hyde, Wilna Fourie, and Mani Padisetti
(1999), “Perceptions of Integrated Marketing Communications among
Markets and Ad Agency Executives in New Zealand,” International
Journal of Advertising, 18(1), 89-119.
Economist (2006), Do we have a story for you! 378, 8461, 1/21/2006
Edell, Jullie A. and Kevin Lane Keller (1989), “The Information Processing of
Coordinated Media Campaigns,” Journal of Marketing Research, 26 (2),
149-163.
Erickson, Gary and Robert Jacobson (1992), “Gaining Comparative Advantage
Through Discretionary Expenditures: The Returns to R&D and
Advertising,” Management Science, 38 (September), 1264-1279.
Farquhar, Peter (1989), “Managing Brand Equity,” Marketing Research,
1(September), 24-33.
Farquhar, Peter (1990), “Managing Brand Equity,” Journal of Advertising
Research, 30(August/September), RC7-RC12.
Farris, Paul W. and Mark S. Albion (1981), “Determinants of the Advertising-toSales Ratio…Applying Method to Madness,” Journal of Advertising
Research, 21 (1), 19-27.
Farris, Paul W. and Robert D. Buzzell (1976), “Relationship between Changes in
Industrial Advertising and Promotion Expenditures and Changes in
Market Share,” Marketing Science Institute Working Paper Series, Report
No. 76-119.
Farris, Paul W. and Robert D. Buzzell (1979), “Why Advertising and Promotional
Costs Vary: Some Cross-Sectional Analysis,” Journal of Marketing, 43,
112-122.
194
Fombrun, J. Charles (1996), Reputation: Realizing Value from the Corporate
Image. Boston, MA: Harvard Business School Press.
Fombrun, J. Charles and Van Riel, Cees B. M. (2004), Fame & Fortune: How
Successful Companies Build Winning Reputations. NY: Prentice Hall.
Fombrun, J. Charles and Shanley, Mark. (1990), “What’s in a Name? Reputation
Building and Corporate Strategy,” Academy of Management Journal,
33(2), 233-258.
Fryxell, Gerald E. and Wang, Jia (1994), “The Fortune Corporate ‘Reputation’
Index: Reputation for What?” Journal of Management, 20 (1), 1-14.
Gamson W., D. Croteau, W. Hoynes, and T. Sasson (1992), “Media Images and
the Social Construction of Reality,” Annual Review of Sociology, 18, 373393.
Gandy, O. H. Jr. (1982), Beyond Agenda Setting: Information Subsidies and
Public Policy. Ablex, Norwood, NJ.
Gedulig, A. (1999), Competitive Reputation. Reputation Management, 5(6), 3436.
Goldberg, Marvine, and Hartwick, Jon (1990), “The Effects of Advertising
Reputation and Extremity of Claim of Advertiser Effectiveness,” Journal
of Consumer Research, 17, 172-179.
Granger, C. W. J. (1969), “Investigating Casual Relations by Econometric Models
and Cross-Spectral Methods,” Econometrica, 37, 424-438.
Grant, T. (1991), “The Resource-Based Theory of Competitive Advantage:
Implications for Strategy Formulation,” California Management Review,
114-135.
Green, W. H. (2000), Econometric Analysis, 4th ed. Upper Saddle river, NJ:
Prentice Hall.
Griffin, Abbie and J.R. Hauser (1996), “Integrating R&D and Marketing: A
195
Review and Analysis of the Literature,” Journal of Product Innovation
Management, 13(3), 191-215.
Grunig, J. E. (1993), “Image and Substance: From Symbolic to Behavioral
Relationships,” Public Relations Review, 19, 121-139.
Grunig, J. E. and T Hunt (1984), Managing Public Relations, New York: Holt,
Rinehart & Winston.
Haedrich, Gunther (1999), “Images and Strategic Corporate and Marketing
Planning,” Journal of Public Relations Research, 5, 2, 83-93.
Hallahan, Kirk. (1999), “Content Class as a Contextual Cue in the Cognitive
Processing of Publicity versus Advertising,” Journal of Public Relations
Research, 11(4), 293-320.
Hammond, Sue Annis and Slocum, John W. Jr. (1996), “The Impact of Prior Firm
Financial Performance on Subsequent Corporate Reputation,” Journal of
Business Ethics, 15(2), 159-165.
Harris, Thomas L. (1998), Value-Added Public Relations: The Secret Weapon of
Integrated Marketing, Lincolnwood, IL: NTC Business Books.
Heckman, J. J. (1979), Sample Selection Bias as a Specification Error,
Econometrica, 47, 153-161.
Hitt, M. A., J. Gimeno, and R. E. Hoskisson (1998), “Current and Future
Research Methods in Strategic Management,” Organizational Research
Methods, 1, 6-44.
Hocj, Stephen J. and Young-Won Ha (1986), “Consumer Learning: Advertising
and the Ambiguity of Product Experience,” Journal of Consumer
Research, 13(2), 221-234.
Hogan, John E., Lemon, Katherine N., and Libai, Barak (2004), “Quantifying the
Ripple: Word-of-Mouth and Advertising Effectiveness,” Journal of
Advertising Research. September, 271-280.
Hon, L. (1997), “What Have You Done for Me Lately? Exploring Effectiveness
in Public Relations,” Journal of Public Relations Research, 9, 1-30.
196
Huey, B. (2002), “Clarifying the Differences between Corporate Brand and
Reputation”, PR Week, 5(1), 6.
Hutton, James G. (1996), “Integrated Marketing Communications and the
Evolution of Marketing Thought,” Journal of Business Research, 37(3),
155-162.
Jack, Neff, “Bottom line on PR: It works, says, P&G,” Advertising Age, 76, 45,
12/7/2005
Jaffe, Adam B. (1986), “Technological opportunity and Spillovers of R&D:
Evidence from Firm’s Patents, Profits, and Market Value,” The American
Economic Review, 76 (5), 984-1001.
Jannis, I. L. and R. Fadner (1965), The Coefficient of Imbalance, In H. Lasswell,
N. Leites, and Associates (Eds.), Language of Politics, 153-169,
Cambridge, MA: MIT Press.
Jeffries-Fox Associates (2000), Toward a Shared Understanding of Corporate
Reputation and Related Concepts: Phase I: Content Analysis. Basking
Ridge, NJ: Report Prepared for the Council of Relations Firms.
Jin, Hyun Seung (2003), “Compounding Consumer Interest: Effects of
Advertising Campaign Publicity on the Ability to Recall Subsequent
Advertisements,” Journal of Advertising, (Winter), 29-41.
Jo, Samsup. (2004), “Effect of Content Type on Impact: Editorial vs.
Advertising,” Public Relations Review, 30, 503-512.
Keith, Timothy Z. (2006), Multiple Regression and Beyond, New York: Pearson.
Keller, Lane Kevin (1993), “Conceptualizing, Measuring, and Managing
Customer-Based Brand Equity,” Journal of Marketing, 57(January), 1-22.
Keller, Lane Kevin (2001), “Mastering the Marketing Communications Mix:
Micro and Macro Perspectives on Integrated Marketing Communication
Programs,” Journal of Marketing Management, 17, 819-847.
Keller, Lane Kevin (2003), Strategic Brand Management: Building, Measuring,
197
and Managing Brand Equity, 2nd ed. Upper Saddle River, NJ: Prentice
Hall.
Kennedy, P. (1985), A Guide to Econometrics (2nd ed.), Cambridge, MA: MIT
Press.
Kim, Yungwook. (2001), “Measuring the Economic Value of Public Relations,”
Journal of Public Relations Research, 13(1), 3-26.
Kirmani, Amna and Valarie Zeithaml (1993), “Advertising, Perceived Quality,
and Brand Image,” in Brand Equity and Advertising: Advertising’s Role in
Building Strong Brands, David A. Aaker and Alexander L. Biel, eds.
Hillsdale, NJ: Laweence Erlbaum Associates, 143-162.
Kitchen, Philip J. and Don Schultz (1999), “A Multi-County Comparison of the
Derive for IMC,” Journal of Advertising Research, 39(1), 21-38.
Klein, Benjamin and Leffler, Keith B. (1981), “The Role of Market Forces in
Assuring Contractual Performance,” Journal of Political Economy, 89, 4,
615-641.
Kotha, Suresh, Shivaram Rajgopal, and Violina Rindova (2001), “Reputation
Building and Performance: An Empirical Analysis of the Top 50 Pure
Internet Firms,” European Management Journal, 19(6), 571-587.
Kreps, D. and R. Wilson (1982), “Reputation and Imperfect Information,”
Journal of Economic Theory, 27, 253-279.
Leone, Robert P. (1995), “Generalizing What is Known about Temporal
Aggregation and Advertising Carryover,” Marketing Science, 14 (3),
G141-150
Leone, Robert P. and Randall L. Shultz (1980), “A Study of Marketing
Generalizations,” Journal of Marketing, 44 (Winter) 10-18.
Lilien, Gary L. (1978), “ADVISOR 2: Modeling the Marketing Mix Decision for
Industrial Products,” Management Science, 25(2), 191-204.
Lilien, Gary L. and John D.C. Little (1976), “The Advisor Project: A Study of
198
Industrial Marketing Budgets,” Sloan Management Review (Spring), 1733.
Lilien, Gary L. and David Weinstein (1984), “An International Comparison of the
Determinants of Industrial Marketing Expenditures,” Journal of Marketing,
48 (Winter), 46-53.
Locken, Barbara and Deborah Roedder-John (1993), “Diluting Brand Beliefs:
When Brand Extensions Have a Negative Impact?” Journal of Marketing,
57 (July), 71-84.
Lodish, Leonard M., Magid Abraham, Stuart Kalmenson, Jennen Livelsberger,
Beth Lubekin, Bruce Richardson and Mary Ellen Stevens (1995), “How
TV Advertising Works: A Meta Analysis of 389 Real World Split Cable
TV Advertising Experiments,” Journal of Marketing Research, 32 (May)
125-139.
Low, George S. (2000), “Correlates of Integrated Marketing Communications,”
Journal of Advertising Research, 40(3), 27-40.
Luo, Xueming and Naveen Donthu (2006), “Marketing’s Credibility: A
Longitudinal Investigation of Marketing Communication Productivity and
Shareholder Value,” Journal of Marketing, 70(October), 70-91.
Margulies, Walter P. (1977), “Make the Most of Your Corporate Identity,”
Harvard Business Review, 55(4), 66-74.
McAlister, Leigh, Raji Srinivasan, and MinChung Kim (2007), “Advertising,
Research and Development, and Systemic Risk of the Firm,” Journal of
Marketing, 71(January), 35-48.
McArthur, David N. and Tom Griffin (1997), “A Marketing Management View of
Integrated Marketing Communications,” Journal of advertising Research,
37(5), 19-26.
McCombs, Maxwell and D. L. Shaw (1972), “The Agenda Setting Function of the
Mass Media,” Public Opinion Quarterly, 36, 176-187.
McDonal, Colin (1992), How Advertising Works. London: The Advertising
Association and NTC.
199
McGoon, Cliff (1998), “Cutting-Edge Companies Use Integrated Marketing
Communication,” Communication World, 16(1), 15-20.
McGuire, Jean B., Sundgren, Alison, and Schneeweis, Thomas (1988),
“Corporate Social Responsibility and Firm Financial Performance,”
Academy of Management Journal, 31, 4, 854-872.
McQuail, Dennis (1985), “Sociology of Mass Communication,” Annual Review of
Sociology, 11, 93-111.
McMillan G. S. and M. P. Joshi (1997), “Sustainable Competitive Advantage and
Firm Performance: The Role of Intangible Resources,” Corporate
Reputation Review, 1, 81-85.
Milgrom, Paul and Roberts, John (1986), “Price and Advertising Signals of
Product Quality,” Journal of Political Economy, 94(4), 796-821.
Mela, Carl F. Sunil Gupta, and Donald R. Lehmann (1997), “The Long-Tern
Impact of Promotions and Advertising on Consumer Brand Choice,”
Journal of Marketing Research, 34 (May), 248-261.
Mizruchi, Mark S. and Schwartz, Michael (1987), Intercorporate Relations: The
Structural Analysis of Business, Cambridge, England: Cambridge
University Press.
Morley, Michael (1998), How to Manage Your Global Reputation,
London: MacMillian Business.
Naik, Prasad A. and Kalyan Raman (2003), “Understanding the Impact of
Synergy in Multimedia Communications,” Journal of Marketing Review,
40(4), 375-388.
Nelson, Philip (1974), “Advertising as Information,” Journal of Political
Economy, 729-754.
Nowak, Glen J. and Joseph Phelps (1994), “Conceptualizing the Integrated
Marketing Communications’ Phenomenon: An Examination of Its Impact
on Advertising Practices and Its Implications for Advertising Research,”
Journal of Current Issues and Research in Advertising, 16(1), 49-66.
200
Ostrom, Charles (1990), Time Series Analysis: Regression Techniques, Sage
Publications.
Page, Graham and Helen Fearn (2005), “Corporate Reputation: What Do
Consumers Really Care About?” Journal of Advertising Research, 45(3),
305-313.
Palda, Kristina S. (1964), The Measurement of Cumulative Advertising Effects,
Englewood Cliffs, NJ: Prentice Hall.
Park, C. Whan, Sandra Milberg, and Robert Lawson (1991), “Evaluation of Brand
Extensions: The Role of Product Level Similarity and Brand Concept
Consistency,” Journal of Consumer Research, 18(September), 185-193.
Parker, Philip M. and Hubert Gatignon (1996), “Order of Entry, Trial Diffusion,
and Elasticity Dynamics: An Empirical Case,” Marketing Letters, 7
(January), 95-109.
Pickton, David and Bob Hartley (1998), “Measuring Integration: An Assessment
of the Quality of Integrated Marketing Communications,” International
Journal of Advertising, 17(4), 285-293.
Podolny, Joel M. (1993), “A Status-Based Model of Market Competition,”
American Journal of Sociology, 98(4), 829-872.
Pollock, T.G. and Rindova, V. (2003), Media Legitimation Effects in the Market
for Initial Public Offerings, Academy of Management Journal, 46(5), 631642.
Preston, L. E. (1981), “Corporate Power and Social Performance: Approaches to
Positive Analysis,” Research in Corporate Social Performance and
Policy: A research Annual, 3, 1-16
Quandit, Richard E. (1964), “Estimating the Effectiveness of Advertising: Some
Pitfalls in Econometric Methods,” Journal of Marketing Research, 1
(May), 51-60.
Raj, S. P. (1985), “Striking a Balance Between Brand’ Popularity and Brand
Loyalty,” Journal of Marketing, 49 (Winter), 523-59.
201
Rao, Ambar G. and Peter B. Miller (1975), “Advertising/Sales Response
Functions,” Journal of Advertising Research, 15 (April), 1-15.
Rao, Vithala R., Manor K. Agarwal, and Denise Dahlhoff (2004), “How is
Manifest Branding Strategy Related to the Intangible Value of a
Corporation?” Journal of Marketing, 68 (October), 126-141.
Reid, Make (2003), “IMC-Performance Relationship: Further Insight and
Evidence from the Australian Marketplace,” International Journal of
Advertising, 22(2), 227-248.
Reputation Institute, http://www.reputationinstitute.com/main/home.php
Ries, Al and Laura Ries (1996), The Fall of Advertising and the Rise of PR, New
York
Roberts, M. S. (1992), “Predicting Voting Behavior via the Agenda-Setting
Tradition,” Journalism and Quarterly, 69, 878-892.
Roberts, Petter W (2001), “Innovation and Firm-Level Persistent Profitability: A
Schumpeterian Framework,” Managerial and Decision Economics, 22 (45), 239-250.
Roberts, Petter W. and Dowling, Grahame R. (2002), “Corporate Reputation and
Sustained Superior Financial Performance,” Strategic Management
Journal, 23, 1077-1093.
Roberts, Petter W. and Hubert Gatignon (1986), “Competitive Effects on
Technology Diffusion,” Journal of Marketing, 50(July), 1-12.
Rumelt, Rechard P. (1987), Theory, Strategy, and Entrepreneurship, in The
Competitive Challenge: Strategies for Industrial Innovation and Renewal,
Teece David (ed.), Cambridge, MA: Ballinger, 137-157.
Salmon, C.T., Reid, L. N., Pokrywcnznski, J., and Willet, W. (1985), “ The
Effectiveness of Advocacy Advertising Relative to News Coverage,”
Communication Research,
12, 546-567.
202
SAS Institute Inc., SAS/ETS Users Guide: The AUTOREG Procedure, Chapter 8,
SAS OnlineDoc, Version 8.
Schultz, Don E. Stanley I. Tannenbaum, and Robert F. Lauterbon (1992),
Integrated Marketing Communications, Lincolnwood, IL: NTC.
Schultz, Don E. (1996), “The Inevitability of Integrated Communications,”
Journal of Business Research, 37(3), 139-146.
Schultz, Don E. and Philip J. Kitchen (1997), “Integrated Marketing
Communications in U.S. Advertising Agencies: An Exploratory Study,”
Journal of Advertising Research, 37(5), 7-18.
Schumann, David W., Hathcote, Jan M., and West, Susan (1991), “Corporate
Advertising in America: A Review of Published Studies on Use,
Measurement, and Effectiveness,” Journal of Advertising, 20(3), 35-55.
Seashore S. E. and E. Yuchman (1967), Factor Analysis of Organizational
Performance,” Administrative Science Quarterly, 12, 372-395.
Shapiro, Carl (1982), “Consumer Information, Product Quality, and Seller
Reputation,” The Bell Journal of Economics, 13, 20-35.
Shapiro, Carl (1983), “Premiums for High Quality Products as Returns to
Reputation,” Quarterly Journal of Economics, 98, 659-679.
Shrivastavas, Paul and Siomkos, George (1989), “Disaster Containment
Strategies,” Journal of Business Strategy, 10 (September-October), 26-31.
Shoemaker, P. J. and S. D. Reese (1991), Mediating the Message: Theories of
Influences on Mass Media Content, White Plains, NY: Longman.
Simon, Marji Frank (1970), “Influence of Brand Name on Attitudes,” Journal of
Advertising Research, 10(3), 28-30.
Simon, J. L., and J. Arndt (1980), “The Shape of the Advertising Response
Function,” Journal of Advertising Research, 20(4), 11-28.
Smallwood, Dennis E. and John Conlisk (1979), “Product Quality in Markets
203
Where Consumers are Imperfectly Informed,” The Quarterly Journal of
Economics, 93, 1-23.
Smith, J. (1995), Understanding the Media: A Sociology of Mass
Communications, Cresskill, NJ: Hampton Press.
Spence, A. M. (1974), Market Signaling: Informational Transfer in Hiring and
Related Screening Process, Cambridge: Harvard University Press.
Smith, Daniel C. and Park, C. Whan (1992), “The Effects of Brand Extensions on
Market Share and Advertising Efficiency,” Journal of Marketing Research,
29(3), 296-313.
Stammerjohan, Clarie, Charles M. Wood, Yumiin Chang, and Esther Thorson
(2005), “An Empirical Investigation of the Interaction Between Publicity,
Advertising, and Previous Brand Attitudes and Knowledge,” Journal of
Advertising, 34(4), 55-56.
Stigler, George J. (1962), “Information in the Labor Market,” Journal of Political
Economy, 70, 49-73.
Sethuraman, Raj and Gerard J. Tellis (1991), “An Analysis of the Trade-Off
Between Advertising and Price Discounting,” Journal of Marketing
Research, 28 (May), 160-174
Shrivastavas, Paul and Siomkos, George (1989), “Disaster Containment
Strategies,” Journal of Business Strategy, 10 (September-October), 26-31.
Stammerjohan, Claire, Charles M. Wood, Yuhmiin Chang, Esther Thorson
(2005), “An Empirical Investigation of the Interaction between Publicity,
Advertising, and Previous Brand Attitudes and Knowledge,” Journal of
Advertising, 34 (4), 55-67
Staw, B. M. and L. D. Epstein (2000), “What Bandwagons Bring: Effects of
Popular Management Techniques on Corporate Performance, Reputation,
and CEO Pay,” Administrative Science quarterly, 45, 523-556.
Stewart, David W. (1996), “Market-Back Approach to the Design of Integrated
204
Communications Programs: A Change in Paradigm and a Focus on
Determinants of Success,” Journal of Consumer Research, 37 (November),
147-153.
Stempel, G. H. (1991), “Where People Get Really Get Most of Their News,”
Newspaper Research Journal, 12(4), 2-9.
Stone, Randy and Mike Duffy (1993), “Measuring the Impact of Advertising,”
Journal of Advertising Research, 33(6), RC8-RC12.
Sudman, Seymour. (1976), Applied Sampling, New York: Academic Press.
Szymansky, D. M., S.G. Bharadwaj, and P.R. Varadarajan (1993), “An Analysis
of the Market Share-Profitability Relationship,” Journal of Marketing, 57,
1-18.
Thorson, Esther and Jeri Moore (1996), “Introduction,” in Integrated
Communication: Synergy of Persuasive Voices, Esther Thorson and Jeri
Moore, eds., Mahwah, NJ: Lawrence Erlbaum, 1-10.
Traynor, Kenneth (1983), “Accounting Advertising,” Journal of Advertising
Research, 23(December), 35-40.
Tversky, Amos and Kahneman, Daniel (1974), “Judgment under uncertainty:
Heuristics and Bias,” Science, 185, 1125-1131.
Tavassoli, Nader T. (1998), “Language in Multimedia: Interaction of Spoken and
Written Information,” Journal of Consumer Research, 25(1), 26-38.
Tavassoli, Nader T. and Yih Hwai Lee (2003), “The Differential Interaction of
Auditory and Visual Advertising Elements with Chinese and English,”
Journal of Marketing Research, 40(4), 468-480.
Telser, Lester G. (1962), “Advertising and Cigarettes,” The Journal of Political
Economy, 70 (October), 471-499.
Tuleja, T. (1985), Beyond the Bottom Line, New York: Facts on File
Vakratsas, Demetrios and Tim Amber (1999), “How Advertising Works: What
Do We Really Know?” Journal of Marketing, 63 (January), 26-43
205
Watrick, S.L. (1992), “The Relationship between Intense Media, Exposure, and
Change in Corporate Reputation,” Business Society, 31, 33-49.
Weighelt, Keith and Camerer, Colin. (1988), “Reputation and Corporate Strategy:
A Review of Recent Theory and Applications,” Strategic Management
Journal, 9(5), 443-454.
Weiss, Allen M., Anderson, Erin, and Maclnnis, Deborah J. (1999), “Reputation
Management as a Motivation for Sales Structure Decisions,” Journal of
Marketing, 63, October, 74-89.
Winner, Russell S. (1979), “An Analysis of the Time-Varying Effects of
Advertising: The Case of Lydia Pinkham,” Journal of Business, 52
(October), 563-576
Winters, Lewis C. (1986), “The Effect of Brand Advertising on Company Image:
Implications for Corporate Advertising,” Journal of Advertising Research,
26 (April-May), 54-59.
Yoon, Eunsan, Hugh J. Guffey, and Valerie Kijewski (1993), “The Effects of
Information and Company Reputation on Intentions to Buy a Business
Service,” Journal of Business Research, 27, 215-228.
Zahay, Debra, James Peltier, Don Schultz, and Abbie Griffin (2004), “The Role
of Transactional versus Relational Data in IMC Programs: Bringing
Customer Data Together,” Journal of Advertising Research, 44(1), 3-18.
206
Vita
Kyung-ran Kim was born as the first daughter to Won-ki Kim and Hyunkoo Lee in Seoul, Korea. Kim completed her bachelor’s from The Seoul
Women’s University and master’s from The Chung-Ang University in Seoul,
Korea. Kim received a master’s degree in Advertising from The University of
Texas at Austin in May 2002.
Permanent address:
10050 Great Hills TRL #1306 Austin, TX 78759
This dissertation was typed by Kyung-ran Kim.
207